CN120072251A

CN120072251A - Auxiliary diagnosis information processing method and auxiliary diagnosis system

Info

Publication number: CN120072251A
Application number: CN202311637548.2A
Authority: CN
Inventors: 梁海; 黄淑兰; 罗显安
Original assignee: Shenzhen Dymind Biotechnology Co Ltd
Current assignee: Shenzhen Dymind Biotechnology Co Ltd
Priority date: 2023-11-30
Filing date: 2023-11-30
Publication date: 2025-05-30

Abstract

The embodiment of the application provides a processing and auxiliary diagnosis system for auxiliary diagnosis information, which utilizes an auxiliary diagnosis result to generate an auxiliary diagnosis report, wherein the auxiliary diagnosis report comprises an abnormal reason distribution diagram and/or a table for indicating at least one abnormal reason causing the abnormality of a test sample and the probability corresponding to each abnormal reason. On the basis, by providing the interactive response function based on the abnormal cause distribution diagram and/or the table, the user can know the diagnosis basis of the abnormal cause diagnosis, so that the abnormal cause diagnosis is reasonable and has improved diagnosis confidence.

Description

Auxiliary diagnosis information processing method and auxiliary diagnosis system

Technical Field

Embodiments of the present application relate to the field of medical technology, and more particularly, to a method for processing auxiliary diagnostic information and an auxiliary diagnostic system.

Background

With the development of test medicine, clinical test projects are more and more diversified, and higher requirements are put on the accuracy and the test efficiency of test results.

At present, when a sample is tested, firstly, a test instrument is used for testing the sample to output test data, and then, a medical staff is used for giving out a test report according to the test data, however, the process is greatly dependent on the knowledge range and clinical experience of the medical staff, so that the accuracy of the test report is difficult to guarantee, and meanwhile, the content presented by the manually-given test report is limited, so that the medical staff is difficult to make an accurate and reliable diagnosis decision according to the test report.

Therefore, how to ensure the accuracy of the inspection report and improve the visualization degree of the inspection report is a problem to be solved in the present day.

Disclosure of Invention

In this context, the embodiment of the application provides a processing method and an auxiliary diagnosis system for auxiliary diagnosis information, which are used for guaranteeing the accuracy of a sample inspection report and improving the visualization degree of the inspection report.

In a first aspect, an embodiment of the present application provides a method for processing auxiliary diagnostic information, including:

The method comprises the steps of obtaining an auxiliary diagnosis report of a test sample, wherein the auxiliary diagnosis report is obtained based on test data of the test sample and sample related information, and comprises an abnormal reason distribution map and/or a table, wherein the abnormal reason distribution map and/or the table are used for indicating at least one abnormal reason causing the abnormality of the test sample and the diagnosis probability of each abnormal reason;

When a selected operation triggered based on the abnormality cause profile/table is acquired, a diagnostic specification of the abnormality cause selected is displayed, the diagnostic specification including at least one of a diagnostic basis, a test item, and an abnormality cause specification of the test sample.

In a second aspect, embodiments of the present application further provide an auxiliary diagnostic system, including:

The sample analyzer is used for detecting the detection sample to obtain detection data;

Auxiliary diagnostic information providing means for obtaining an auxiliary diagnostic report based on the test data of the test sample and sample-related information, and

The auxiliary diagnostic information processing apparatus realizes the steps of the auxiliary diagnostic information processing method as described above.

According to the auxiliary diagnosis information processing method provided by the embodiment of the application, the auxiliary diagnosis result is utilized to generate the auxiliary diagnosis report, the auxiliary diagnosis report comprises an abnormal reason distribution diagram and/or a table and is used for indicating at least one abnormal reason causing the abnormality of the test sample and the probability corresponding to each abnormal reason, compared with the auxiliary diagnosis report of a text version, a doctor does not need to read the text line by line, but can intuitively know the abnormal reason in a diagram and/or table mode, and the reliability of the abnormal reason is increased by increasing the diagnosis probability for the abnormal reason, and meanwhile, the doctor can be helped to distinguish the diagnosis probability and the possibility of each abnormality. On the basis, by providing the interactive response function based on the abnormal cause distribution diagram and/or the table, the user can know the diagnosis basis of the abnormal cause diagnosis, so that the abnormal cause diagnosis is reasonable and has improved diagnosis confidence.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a block diagram of an auxiliary diagnostic system according to an embodiment of the present application;

FIG. 2 is a flowchart illustrating a method for processing auxiliary diagnostic information according to an embodiment of the present application;

FIG. 3 is a schematic diagram of an interface for displaying diagnostic instructions according to an embodiment of the present application;

FIG. 4 is a schematic diagram of an interface for providing an auxiliary diagnostic report according to an embodiment of the present application;

FIG. 5 is a schematic diagram of an interface for displaying diagnostic instructions according to an embodiment of the present application;

FIG. 6 is a schematic diagram of an interface for providing an auxiliary diagnostic report according to an embodiment of the present application;

FIG. 7 is a schematic diagram of an interface for providing an auxiliary diagnostic report according to an embodiment of the present application;

FIG. 8 is a schematic diagram of an anomaly cause distribution table according to an embodiment of the present application;

FIG. 9 is an interface diagram for supplementing the cause of an abnormality according to an embodiment of the present application;

FIG. 10 is a schematic diagram of a sample related information interface according to an embodiment of the present application;

FIG. 11 is an interface diagram of sample information according to an embodiment of the present application;

FIG. 12 is a schematic interface diagram of a clinical symptom treatment provided by an embodiment of the present application;

FIG. 13 is a schematic diagram of an interface for providing an auxiliary diagnostic report according to an embodiment of the present application;

Fig. 14 is a schematic structural diagram of an auxiliary diagnostic information providing apparatus according to an embodiment of the present application;

FIG. 15 is a schematic diagram of a target knowledge graph according to an embodiment of the present application;

fig. 16 is a schematic diagram of a target knowledge graph corresponding to suppurative inflammation diseases according to an embodiment of the present application;

FIG. 17 is a schematic diagram of the data to be diagnosed according to the embodiment of the present application;

fig. 18 is an exemplary prevalence radar chart provided by an embodiment of the application.

In the drawings, the same or corresponding reference numerals indicate the same or corresponding parts.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The terms first and second and the like in the description of embodiments of the application, in the claims and in the above-described figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented, for example, in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be understood that the term "and/or" as used herein is merely an association relationship describing the associated object, and means that there may be three relationships, e.g., a and/or B, and that there may be three cases where a exists alone, while a and B exist together, and B exists alone. "/" indicates a relationship of "or".

In the related art, when a sample is tested, the test instrument firstly tests the sample to output test data, and then medical staff issues a diagnosis report according to the test data. However, the inventors have found that the complex relationships between different parameters, biomarkers and diseases involved in the test report are very challenging to analyze manually, it is difficult for medical personnel to quickly extract key information from the various parameters, it is more inefficient to use the information sufficiently, and the content presented by the artificially presented diagnostic report is limited and less visual, making it difficult for medical personnel to make accurate and reliable diagnostic decisions from the diagnostic report.

Meanwhile, in the inspection process, medical staff often lacks deep analysis and accurate judgment on diagnosis results, and when a diagnosis report is sent out, the medical staff is greatly dependent on the knowledge range and clinical experience of the medical staff, the knowledge range and clinical experience of the medical staff may be limited, the clinical significance of each inspection item is likely to be not deeply understood, and all possible factors and links related to disease diagnosis cannot be comprehensively considered. Moreover, due to the difference in education level of medical staff, the same test result may obtain different interpretations and conclusions, and the subjectivity and the difference may affect the accuracy of diagnosis, so that the accuracy of a diagnosis report is difficult to ensure.

In addition, medical personnel are burdened with a great deal of effort daily from an scalability point of view and are not sensitive to updates of medical knowledge, and thus manual testing has great limitations when dealing with expanding large amounts of data, different data sources, and ever-updated medical knowledge.

Accordingly, an embodiment of the present application provides a process for assisting in diagnosis information to solve at least one of the above problems. Embodiments of the present application will be described below with reference to the accompanying drawings.

Fig. 1 is a schematic diagram of an auxiliary diagnostic system according to an embodiment of the present application. As shown in fig. 1, the application scenario provided by the embodiment of the present application includes a sample analyzer 101, an auxiliary diagnostic information processing device 102, and an auxiliary diagnostic information providing device 1023. The auxiliary diagnostic information processing apparatus 102 and the auxiliary diagnostic information providing apparatus 103 are computer program products, such as various application programs, based on a computer program flow, for implementing an auxiliary diagnostic function.

Auxiliary diagnostic information providing apparatus 103 which implements an auxiliary diagnostic information providing method to implement an auxiliary diagnostic function. The auxiliary diagnostic information processing apparatus 102 provides a method for processing auxiliary diagnostic information to process the auxiliary diagnostic information to form an auxiliary diagnostic report.

In some embodiments, the auxiliary diagnostic information providing apparatus 103 and the auxiliary diagnostic information processing apparatus 102 may be integrated into one terminal device, where one auxiliary diagnostic information providing method and one auxiliary diagnostic information processing method are implemented.

In some embodiments, the auxiliary diagnostic information providing means 103, the processing means 102 of the auxiliary diagnostic information may also be integrated with the sample analyzer 101, such as a sample analyzer loaded with a corresponding computer program product.

In some embodiments, the processing means 102 of the auxiliary diagnostic information may be arranged to be communicatively connected to an output interface of an application system in the sample analyzer 101 for performing a test analysis on the sample, for obtaining test data from the sample analyzer 101 obtained after the test analysis has been performed on the sample to be tested. The sample to be tested is a sample which is taken from the body of a sample provider and contains various biological cell information or other biological information, such as a blood sample, a urine sample and other body fluid (hydrothorax and ascites, cerebrospinal fluid, serosal cavity effusion and synovial fluid) samples.

Specifically, the auxiliary diagnosis information processing device 102 obtains test data obtained by testing and analyzing a sample to be tested by the sample analyzer 101, sends the test data to the auxiliary diagnosis information providing device 103, and the auxiliary diagnosis information providing device 103 pre-processes the test data to obtain to-be-diagnosed information, wherein the to-be-diagnosed information comprises at least one of to-be-tested items, numerical information corresponding to the to-be-tested items and basic information corresponding to the sample to be tested, and matches the to-be-diagnosed information based on a target knowledge graph corresponding to the current test items, so that abnormal information corresponding to the sample to be tested is obtained according to a matching result, and auxiliary diagnosis information is obtained.

The auxiliary diagnostic information providing apparatus 103 transmits auxiliary diagnostic information to the auxiliary diagnostic information processing apparatus 102, the auxiliary diagnostic information processing apparatus 102 acquires an auxiliary diagnostic report of a test sample, the auxiliary diagnostic report being obtained based on test data of the test sample and sample related information, the auxiliary diagnostic report including an abnormality cause distribution map and/or table for indicating at least one abnormality cause causing abnormality of the test sample and a diagnostic probability of each abnormality cause, and when a selection operation triggered based on the abnormality cause distribution map/table is acquired, displays a diagnostic specification of the selected abnormality cause, the diagnostic specification including at least one of a diagnostic basis of the test sample, a test item, and an abnormality cause specification.

In this way, the auxiliary diagnostic information providing apparatus 103 in the embodiment of the present application matches the information to be diagnosed by using the knowledge graph, so as to obtain the abnormal information of the sample provider, and compared with the manual analysis, the auxiliary diagnostic information providing apparatus 102 outputs a diversified auxiliary diagnostic report, which has a higher degree of visualization, so that the user can more intuitively understand the condition of the possible existing or potential disorder of the patient to which the sample to be tested belongs by looking at the auxiliary diagnostic report, and in the case of determining that the abnormality exists, the accurate auxiliary diagnostic result can be obtained by using the diagnosis basis provided in the auxiliary diagnostic report without depending on the personal experience level of the test medical staff, on one hand, the test result can be improved more accurately, and on the other hand, the auxiliary diagnostic report includes an abnormal cause distribution graph and/or table for indicating at least one abnormal cause causing the abnormality of the test sample and the probability corresponding to each abnormal cause, and the doctor does not need to read the text line by line, can intuitively understand the abnormal cause by increasing the diagnostic probability of the abnormal cause, and, by increasing the reliability of the abnormal cause, and can help the doctor to distinguish each abnormal cause and the probability of abnormal cause. On the basis, the auxiliary diagnosis report not only provides the abnormal reasons of the user, but also provides the interactive response function based on the abnormal reason distribution diagram and/or the table, so that the user obtains the diagnosis basis for knowing the diagnosis of the abnormal reasons, the diagnosis of the abnormal reasons is reasonable and has improved diagnosis confidence.

Alternatively, the auxiliary diagnostic information providing apparatus 103 may comprehensively consider the multifaceted data of the sample provider, such as clinical information data representing individual differences of the sample provider, typically including gender, age, medical history, etc., in determining the auxiliary diagnostic category information. The auxiliary diagnosis information providing apparatus 103 may be used in a plurality of stages, one stage is that the sample analyzer 101 takes into account the clinical information data of the sample provider to calibrate the obtained sample test data in the process of testing and analyzing the sample to be tested by the sample analyzer 101, and the other stage is that the auxiliary diagnosis information providing apparatus 103 directly obtains the clinical information data of the sample provider, and in the process of matching the information to be diagnosed with the target knowledge graph to obtain the matching result, the clinical information data of the sample provider is further comprehensively considered to calibrate the abnormal information corresponding to the sample to be tested. In some embodiments, the use of clinical information data by the sample provider by the auxiliary diagnostic information providing device 103 is provided including the second stage described above, and the auxiliary diagnostic information providing device 103 is communicatively connected to a test data system (Laboratory Information System, LIS), which typically includes application terminals disposed at different locations of a hospital's diagnosis guiding table, clinical laboratory, etc., and is operable to receive test data, enter and store patient test data, and assist the hospital in information management. The auxiliary diagnostic information providing apparatus 103 may obtain clinical information data of a specified category of the sample provider directly from the test data system.

In order to facilitate understanding of the technical implementation of the auxiliary diagnostic information providing apparatus 103 provided in the embodiment of the present application, in the description of the present application, a specific example will be mainly described in detail by taking a sample to be tested as a blood sample, and the corresponding sample analyzer 101 is shown by taking a blood cell analyzer as an example, but this should not be taken as a limitation in practical application. The sample analyzer 21 may also be a biochemical analyzer, an immunoassay analyzer, a coagulation analyzer, or the like.

In other embodiments, the test data for the sample to be tested may be from a plurality of different sample analyzers 101, such as a blood cell analyzer, a biochemical analyzer, and an immunoassay analyzer. Accordingly, the processing of the auxiliary diagnostic information 102 and the sample test data acquired by the auxiliary diagnostic information providing apparatus 103 may include one or more of blood cell analysis data, biochemical analysis data, and immunological analysis data.

The following describes embodiments of the present application and how the technical solutions of the present application solve the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

Fig. 2 is a flowchart illustrating a method for processing auxiliary diagnostic information according to an embodiment of the present application. As shown in fig. 2, the method for processing auxiliary diagnostic information provided by the embodiment of the application includes:

step 202, obtaining an auxiliary diagnosis report of the test sample, wherein the auxiliary diagnosis report is obtained based on the test data of the test sample and the sample related information, and comprises an abnormal reason distribution map and/or a table, and the abnormal reason distribution map and/or the table are used for indicating at least one abnormal reason causing the abnormality of the test sample and the diagnosis probability of each abnormal reason.

Specifically, the auxiliary diagnosis information providing device is used for obtaining the test data of the sample to be tested and the sample related information, processing the test data and the sample related information to obtain the information to be diagnosed, obtaining the target knowledge graph, matching the information to be diagnosed with the target knowledge graph to obtain a matching result, and outputting an auxiliary diagnosis report according to the matching result. The auxiliary diagnostic information providing device transmits the auxiliary diagnostic report to the auxiliary diagnostic information processing device to perform the auxiliary diagnostic report processing.

In this embodiment, compared with human analysis, the auxiliary diagnosis information providing device has a wider knowledge range covered by the knowledge graph, so that the influence of subjective factors of medical staff can be avoided, key information can be rapidly extracted, deep analysis and accurate judgment can be performed, and efficiency and accuracy can be guaranteed.

The auxiliary diagnostic information processing means acquires auxiliary diagnostic information on the test sample and processes the auxiliary diagnostic information as an auxiliary diagnostic report. When a doctor's instruction to view the auxiliary diagnostic report of the test sample is obtained, the auxiliary diagnostic report is displayed for viewing by the doctor.

The auxiliary diagnostic report may include an abnormality cause profile, or may include an abnormality cause profile and an abnormality cause profile. Wherein the abnormality cause distribution map graphically represents probability distribution of the abnormality cause. The abnormality cause distribution map includes a representation area for representing the cause of the abnormality, and probabilities of different causes of the abnormality may be represented by at least one of the area, the color, and the shape of the abnormality cause representation area.

The abnormality cause distribution table represents probability distribution of abnormality causes in a table form, and at least two packets and two columns of the abnormality cause distribution table are respectively an abnormality cause and a probability, and the probability of different abnormality causes is represented by the numerical value of the probability.

In this embodiment, by using the abnormality cause distribution map and/or table, compared with the text representation method, the doctor does not need to read the text line by line, but can intuitively understand the abnormality cause by using the map and/or table method, and by adding the diagnosis probability to the abnormality cause, the reliability of the abnormality cause is increased, and at the same time, the doctor can be assisted in distinguishing the possibility of each abnormality cause.

Step 204, when a selected operation triggered based on the abnormality cause profile/table is acquired, displaying a diagnosis specification of the selected abnormality cause, the diagnosis specification including at least one of a diagnosis basis of the test sample, a test item, and an abnormality cause specification.

In this embodiment, the abnormality cause distribution diagram and/or table of the auxiliary diagnosis report can intuitively understand the abnormality cause and the diagnosis probability of each abnormality cause, and based on this, the user can trigger the selection operation based on the abnormality cause distribution diagram/table, so as to display the diagnosis description indicating the abnormality cause that is viewed. The diagnostic instructions include at least one of diagnostic basis, test item, and explanation of cause of abnormality.

The diagnosis basis is the basis for the auxiliary diagnosis information providing device to diagnose the abnormal cause, and generally comprises the abnormal index for analyzing the abnormal cause in the inspection data and the sample related information, so that the diagnosis of the abnormal cause is reasonable and has improved confidence of auxiliary diagnosis.

The check item refers to a check item that is required to further verify the cause of the abnormality. By providing the examination items, the user can understand the examination items to be done next, and also provide the doctor with the examination plan next.

The explanation of the cause of abnormality includes the cause of occurrence of abnormality, abnormal symptoms, and the like.

In the present embodiment, by providing the interactive response function based on the abnormality cause profile and/or table, the user is made aware of the diagnosis explanation of the abnormality cause diagnosis, making the abnormality cause diagnosis rational.

According to the auxiliary diagnosis information processing method, the auxiliary diagnosis result is utilized to generate the auxiliary diagnosis report, the auxiliary diagnosis report comprises the abnormal cause distribution diagram and/or the table and is used for indicating the probability that at least one abnormal cause and each abnormal cause of the abnormal test sample are corresponding to each other, compared with the auxiliary diagnosis report with a text version, a doctor does not need to read the text line by line, the abnormal cause can be intuitively understood through a diagram and/or the table mode, and the diagnosis probability is increased for the abnormal cause, so that the reliability of the abnormal cause is increased, and meanwhile, the doctor can be helped to distinguish the diagnosis probability and the possibility of each abnormal. On the basis, by providing the interactive response function based on the abnormal cause distribution diagram and/or the table, the user can know the diagnosis basis of the abnormal cause diagnosis, so that the abnormal cause diagnosis is reasonable and has improved diagnosis confidence.

In one embodiment, the auxiliary diagnostic report may include only abnormal cause distribution graphs for displaying the auxiliary diagnostic result. In this embodiment, the abnormality cause distribution map includes respective abnormality cause correspondence expression areas. Each of the indication areas is used to indicate a cause of an abnormality. In one embodiment, in order to enable the user to visually observe the probability height relationship of each anomaly cause, the representation areas corresponding to each anomaly cause of the anomaly cause distribution map are arranged in order of probability height.

In another embodiment, in order to enable the user to know the probability level through the graphic, the probability level that the representation area may exhibit the cause of the abnormality through at least one of the area, the color, and the shape. For example, the larger the probability, the larger it represents the occupied area of the region. Wherein the shape of the representation area is different according to the form of the graph adopted by the abnormality cause distribution graph.

In one embodiment, the auxiliary diagnostic information providing device may provide an auxiliary diagnostic result including a plurality of abnormal reasons, and in a case where the abnormal reasons are more, the reference meaning of some abnormal reasons with lower probability is not great, and the processing device of the auxiliary diagnostic information may generate an abnormal reason distribution map and/or table according to the first N abnormal reasons with highest probability. In one embodiment, if the abnormality cause distribution map and/or table is generated from the first 10 abnormality causes having the highest probability, the first 10 abnormality causes having the highest probability are displayed in the abnormality cause distribution map. It is understood that if the number of abnormality causes provided by the processing device for the auxiliary diagnostic information is smaller than N, the differences are generated based on all the abnormality causes. It will therefore be appreciated that the sum of the diagnostic probabilities of all of the abnormality causes in the abnormality cause profile and/or table is not greater than 1.

In one embodiment, the abnormality cause profile is used to indicate a diagnostic probability of the cause of the abnormality, and thus the abnormality cause profile is more suitable for use in a visualization that embodies scale. In some embodiments, the abnormality cause profile includes any one of a pie chart, a radar chart, and a chord chart, the abnormality cause profile exhibiting, by at least one of area, angle, color, and shape, a probability of an abnormality cause, a number of directed edges, and a frequency of occurrence of the abnormality cause.

Wherein, cake patterns and variants thereof, such as standard cake patterns, ring patterns, nested cake patterns, rose patterns, ring patterns and cake patterns collocation time axis patterns, can be adopted.

The radar map and its deformation map may be also used, such as standard radar map, filling radar map and worm hole radar map.

Chord graphs and variants thereof, such as standard chord graphs, multi-list chord graphs, and non-bandaged chord graphs, may also be employed.

Taking a pie chart as an example, the pie chart comprises a plurality of fan-shaped areas, each fan-shaped area is a representation area of an abnormal cause, and the fan-shaped area and the color represent the probability of the abnormal cause. And the sector area can be adjusted according to the circle center angle and the color.

Taking a rose diagram as an example, the rose diagram comprises a plurality of fan-shaped areas, wherein each fan-shaped area is a representation area of an abnormal cause, and the fan-shaped area and the color represent the probability of the abnormal cause. The sector area can be adjusted according to the radius length, the circle center angle and the color.

In one embodiment, the abnormal cause distribution diagram is further used for indicating the number of directed edges corresponding to the sample to be tested and the occurrence frequency corresponding to the abnormal cause, the number of the directed edges is used for indicating the number of clinical findings corresponding to each abnormal cause in the target knowledge graph, and the occurrence frequency of the abnormal cause is used for indicating the occurrence times of the correspondence between the clinical findings of the abnormal cause and the abnormal information in the literature corresponding to the target knowledge graph.

Specifically, the target knowledge graph includes nodes and directed edges connecting the nodes.

The nodes are of two types, one is an abnormal information node obtained from each medical guideline, the abnormal information node contains information such as follow-up examination, treatment scheme and the like of each abnormal item, and the other is a clinically seen node which is the rise/fall of each index of the examination, such as leucocyte rise and the like.

In practical application, the clinically seen nodes and the abnormal information nodes are connected through the directed edges, and the directions of the directed edges are used for indicating the relation between the clinically seen nodes and the abnormal information, namely the directions of the directed edges are used for indicating the prompt of the clinically seen nodes to the abnormal information.

In order to enable a user to intuitively know the probability distribution relation of the abnormal reasons, the representation areas corresponding to the abnormal reasons in the probability distribution diagram of the abnormal reasons are sequentially arranged according to the probability.

On this basis, the user performs a selection operation in the abnormality cause display area to trigger and display a diagnostic specification of the abnormality cause. When a selected operation triggered based on the indication area on the abnormal cause distribution diagram is acquired, displaying the diagnosis description of the abnormal cause corresponding to the indication area in a popup window mode according to the triggering position. The selecting operation includes at least one of moving the cursor to the representation area, clicking a selection control in a dwell time of the cursor in the representation area exceeding a predetermined time, and right-clicking a selection option.

In this embodiment, the diagnostic instructions are displayed in the form of a floating pop-up window that pops up in response to a user's selection. In some embodiments, the popped-up floating frame can be adaptively adjusted in position and size according to the position of the mouse, for example, when the mouse is on the left side of the center of the auxiliary diagnostic radar chart, the pop-up window is displayed on the left side, the right frame of the pop-up window is abutted against the position of the mouse cursor, and conversely, the pop-up window is on the right side.

In another embodiment, in order for the diagnostic instructions to more intuitively exhibit the interactive relationship of the triggering operations of the presentation area, the floating window of the diagnostic instructions is adaptively adjusted according to the position of the interactive operations. For example, when the mouse abnormality cause profile is on the left side, a floating pop-up window is also displayed on the right side, and the display area in the abnormality cause profile is highlighted. When the mouse trigger is on the right side of the abnormality cause profile, the floating popup window is also displayed on the left side and highlights the representation area in the abnormality cause profile. Thus, the user can intuitively understand the selected abnormality cause and the diagnosis corresponding to the abnormality cause. The display effect is shown in fig. 3.

In another embodiment, the size of the floating bullet window is fixed, but when the content of the diagnosis explanation of some abnormal reasons is more, the display is incomplete, at this time, the content of the diagnosis explanation can be cut off, and the cut-off characters are added with omitted signs. Further, the user may display a complete diagnostic statement by continuing to trigger the floating popup.

In summary, there are five ways to trigger a diagnostic explanation of the cause of an abnormality through the abnormality cause profile:

first, when a cursor is moved to a display area of an abnormality cause is acquired, a diagnostic specification of the abnormality cause corresponding to the display area is displayed.

Second, when a click operation is acquired on a display area of an abnormality cause, a diagnostic specification of the abnormality cause corresponding to the display area is displayed.

Third, when the stay time of the cursor in the display region exceeds a predetermined time, a diagnostic specification of the cause of the abnormality corresponding to the display region is displayed.

Fourth, when the selection control is clicked, a diagnostic specification of the cause of the abnormality corresponding to the display area is displayed. In this embodiment, a selection control may be provided on each of the representation areas of the abnormality cause profile.

Fifth, when the right key triggers the selection option, a diagnosis explanation of the abnormality cause corresponding to the display area is displayed. In this embodiment, a selection option may be added, where the selection option pops up by clicking a right button for the user to select.

By any of the above means, the user can intuitively know the diagnosis instruction of the cause of the abnormality through the display interface.

In another embodiment, when a selected operation triggered based on the presentation area on the abnormality cause profile is acquired, a diagnostic specification of the abnormality cause is displayed in a diagnostic specification area of the auxiliary diagnostic report.

As shown in fig. 4, the auxiliary diagnostic report includes an abnormality cause distribution map and a diagnostic specification region that is blank when any one of the display regions is not selected below the abnormality cause distribution map. When a representation area is selected in the abnormality cause distribution map, a diagnosis specification of the selected abnormality cause is displayed in a diagnosis specification area.

Specifically, when the cursor is moved to the representation area, or a clicking operation of the representation area is obtained, or the stay time of the cursor in the representation area exceeds a predetermined time, or the selection control is clicked, or the right key triggers the selection option, the representation area is selected, and at the same time, a diagnosis description of the cause of the selected abnormality is displayed in the auxiliary diagnosis description area. It will be appreciated that as the selected presentation area increases, so does the diagnostic profile in the diagnostic profile area.

In the present embodiment, by providing the diagnostic specification area for displaying the diagnostic specification of the abnormality cause corresponding to the selected presentation area, the content displayed in the diagnostic specification area can be visually linked with the selection operation of the abnormality cause distribution map, and the diagnostic specification of the selected abnormality cause can be continuously presented in the diagnostic specification area. The doctor only needs to select which abnormality cause is collected according to experience, and the diagnosis description of the abnormality cause is output through the selection operation of the abnormality cause distribution diagram as the interpretation of the auxiliary diagnosis description, thereby improving the operation convenience. Meanwhile, the interpretation explanation of the abnormal reasons adopted by the regular diagnostic explanation region can be conveniently displayed to the patient. In order to make the result of the selection operation more visual, in one embodiment, when the selection operation triggered by the representation area on the abnormal cause distribution diagram is acquired, the selected representation area is switched from the original state to the highlighting state, wherein the highlighting mode comprises any one of increasing the representation area, highlighting the representation area, adding a frame to the representation area and popping the representation area outwards for a preset distance.

In the original state, the representation areas are all displayed by adopting initial display parameters. And when a selected operation triggered based on the representation area on the abnormality cause profile is acquired, when the selected representation area is switched from the original state to the highlighted state. The highlighting serves to distinguish between selected and unselected presentation areas so that the user can intuitively observe the selected presentation area.

An example of highlighting may be to highlight a selected presentation area by presenting a magnification effect of the presentation area from an unselected state to a selected state in order to enlarge the presentation area.

An example of highlighting may also be to add a border to the presentation area, whereby the selected presentation area is highlighted compared to the unselected presentation areas due to the addition of the border compared to the other unselected presentation areas.

An example of highlighting may also be to pop out the presentation area a preset distance. The display area is highlighted by presenting a movement effect of the presentation area from the unselected state to the selected state.

An example of highlighting may also be highlighting the representation area. The selected presentation area is highlighted as compared to the other unselected presentation areas.

In this embodiment, by highlighting the selected indication area, the indication area of the selected operation is made more intuitive, and the user can operate the abnormality cause desired to be selected through the abnormality cause distribution map.

In another embodiment, when a cancel operation of the selected representation area is acquired, the representation area is restored to an original state, the cancel operation comprises at least one of separating a cursor from the representation area, clicking the selected representation area, clicking a cancel control and right-click operation, and canceling display of a diagnostic specification of an abnormality cause corresponding to the representation area.

In some embodiments, if the user has finished looking up the diagnostic specification of the cause of the abnormality corresponding to the presentation area, the diagnostic specification of the cause of the abnormality may be canceled by the cancel selection operation. In other embodiments, if the user selects not to use the cause of the abnormality by looking at the cause of the abnormality corresponding to the presentation area, the cause of the abnormality may be deselected by deselecting, and the diagnostic specification of the cause of the abnormality may be displayed.

When a cancel operation of the selected presentation area is acquired, the presentation area is restored to the original state, the presentation area is not highlighted, i.e., is in the non-selected state, which can be observed from the appearance of the presentation area, and at the same time, the diagnostic specification is canceled from being displayed.

Specifically, one example of the deselect operation may be to move the cursor away from the presentation area. When the cursor is moved away from the display area, the display area is restored to the original state, and the floating popup window is closed to cancel the display of the diagnostic specification of the cause of the abnormality, or the diagnostic specification of the cause of the abnormality of the diagnostic specification area is deleted.

Another example of a deselect operation may be a click operation on the selected presentation area. When the clicking operation is performed on the selected indication area, the indication area is restored to the original state, and the suspended popup window is closed to cancel the display of the diagnostic explanation of the cause of the abnormality or to delete the diagnostic explanation of the cause of the abnormality of the diagnostic explanation area.

Yet another example of a deselect operation may be clicking on a cancel control. By setting a cancel control in each selected presentation area, when an operation of the cancel control is acquired, the presentation area is restored to the original state, and the suspended popup window is closed to cancel the display of the diagnostic specification of the cause of the abnormality, or the diagnostic specification of the cause of the abnormality of the diagnostic specification area is deleted.

As yet another example of a deselect operation, a cancel operation may also be triggered for a right key. The option list includes a cancel option by right-key triggering, and when a right-key triggering cancel operation is acquired, the presentation area is restored to the original state, the floating popup window is closed to cancel the display of the diagnostic specification of the cause of the abnormality, or the diagnostic specification of the cause of the abnormality of the diagnostic specification area is deleted.

In this embodiment, by canceling the selected indication area, the diagnosis description of the abnormality cause corresponding to the indication area is displayed in a linked manner, so that the doctor can conveniently use and cancel the use process of the auxiliary diagnosis conclusion.

In another embodiment, the auxiliary diagnostic report may include only an abnormality cause distribution table in the form of a table. The table may include at least two examples, an abnormality cause and a diagnosis probability, respectively. So that the user can know the diagnosis conclusion provided by the auxiliary diagnosis through the abnormal cause distribution table.

In one embodiment, in order to enable a user to intuitively observe the probability height relationship of each anomaly cause, each anomaly cause in the anomaly cause distribution table is arranged in order of probability height.

In one embodiment, the auxiliary diagnostic information providing device may provide an auxiliary diagnostic result including a plurality of abnormal reasons, and in a case where the abnormal reasons are more, the reference meaning of some abnormal reasons with lower probability is not great, and the processing device of the auxiliary diagnostic information may generate an abnormal reason distribution map and/or table according to the first N abnormal reasons with highest probability. In one embodiment, if the abnormality cause distribution map and/or table is generated from the first 10 abnormality causes having the highest probability, the first 10 abnormality causes having the highest probability are displayed in the abnormality cause distribution map. It is understood that if the number of abnormality causes provided by the processing device for the auxiliary diagnostic information is smaller than N, the differences are generated based on all the abnormality causes. Constant cause probability distribution maps and/or tables. It will therefore be appreciated that the sum of the diagnostic probabilities of all of the abnormality causes in the abnormality cause profile and/or table is not greater than 1.

In one embodiment, when a selected operation on a cell triggered based on an abnormal cause distribution table is acquired, a diagnostic specification of the abnormal cause corresponding to the cell is displayed in a popup window form according to the trigger position.

The specific mode of the selection operation is similar to the selection operation mode based on the abnormal reason distribution diagram, the selection operation comprises the steps of moving a cursor to a cell of the abnormal reason, clicking the cell of the abnormal reason, clicking a selection control of the abnormal reason when the stay time of the cursor in the cell of the abnormal reason exceeds a preset time, and triggering at least one of selection options by a right key. The specific selection process is not described here in detail.

The process of displaying the diagnostic explanation of the abnormality cause corresponding to the cell in the form of a popup window is similar to the process of displaying the diagnostic explanation of the abnormality cause in the form of a popup window in the abnormality cause distribution map, and will not be described here. The display effect is shown in fig. 5. In this embodiment, when the user passes through a certain cell in the abnormality cause distribution table, the diagnostic specification of the abnormality cause corresponding to the cell is displayed through the popup window, and the user can intuitively know the diagnostic specification of the abnormality cause through the display interface.

Optionally, in some embodiments, the selecting operation includes a first type of selecting operation and a second type of selecting operation, where the first type of selecting operation and the second type of selecting operation correspond to different operation modes. When the selected operation triggered by the cells based on the abnormal cause distribution table is obtained, displaying the diagnosis description of the abnormal cause corresponding to the cells in a popup window mode according to the triggering position; and when a second selected operation triggered by the cells on the abnormal cause distribution table is acquired, displaying the diagnosis description of the abnormal cause in the diagnosis description area of the auxiliary diagnosis report.

The first selecting operation and the second selecting operation may be set according to actual application requirements, and are not limited herein. For example, the first selection operation may be one or more of a cursor movement to the cell, a click operation on the cell, a dwell time of the cursor on the cell exceeding a predetermined time, and the second selection operation may be one or more of a click selection control, a right-click trigger selection option, and the like.

Optionally, the selecting operation further includes a third type of selecting operation, and when the third selecting operation triggered by the cells on the abnormal cause distribution table is acquired, the diagnostic description of the abnormal cause corresponding to the cells may be displayed in a popup window according to the triggering position, and the diagnostic description of the abnormal cause may be displayed in a diagnostic description area of the auxiliary diagnostic report.

In another embodiment, when a selection operation of a cell triggered based on the abnormality cause distribution table is acquired, a diagnosis description of an abnormality cause corresponding to the cell is displayed in a diagnosis description area, the selection operation including a movement of a cursor to the cell of the abnormality cause, a click operation of the cell of the abnormality cause, a stay time of the cursor in the cell of the abnormality cause exceeding a predetermined time, clicking a selection control of the abnormality cause, a right click triggering at least one of selection options, the diagnosis description area being below the abnormality cause distribution table.

The specific manner of displaying the diagnostic instructions in the diagnostic instruction area in conjunction with the selection operation in the abnormality cause distribution table is similar to the specific manner of displaying the diagnostic instructions in the diagnostic instruction area in conjunction with the selection operation in the abnormality cause distribution table, and will not be described in detail here. The display effect is shown in fig. 6.

In the present embodiment, by providing the diagnosis instruction area for displaying the diagnosis instruction of the abnormality cause corresponding to the selected indication area, the content displayed in the diagnosis instruction area can be visually linked with the selection operation of the abnormality cause distribution table, and the diagnosis instruction of the selected abnormality cause can be continuously presented in the diagnosis instruction area. The doctor only needs to select which abnormality cause is collected according to experience, and the diagnosis description of the abnormality cause is output through the selection operation of the abnormality cause distribution table as the interpretation of the auxiliary diagnosis description, thereby improving the operation convenience. Meanwhile, the interpretation explanation of the abnormal reasons adopted by the regular diagnostic explanation region can be conveniently displayed to the patient.

In another embodiment, the auxiliary diagnostic report includes an abnormality cause distribution map, an abnormality cause distribution table, and a diagnostic specification area. The abnormality cause distribution map may be located above or to the left of the abnormality cause distribution map, and the diagnosis instruction area may be located below the abnormality cause distribution table. As shown in fig. 7, the abnormality cause distribution map may be located above the abnormality cause distribution map, and the diagnosis specification area may be located below the abnormality cause distribution table.

The abnormality cause distribution map can be visualized from the figure, and the abnormality cause distribution can be intuitively known. When a trigger operation based on the abnormality cause distribution map is acquired, a diagnostic specification indicating the abnormality cause corresponding to the region is displayed in a pop-up window form according to the trigger position. The selection operation comprises at least one of cursor movement to the representation area, clicking operation on the representation area, clicking a selection control when the residence time of the cursor in the representation area exceeds a preset time, and right key triggering selection options.

When a selected operation triggered by the representation area on the abnormal cause distribution diagram is acquired, the selected representation area is switched from an original state to a highlighting state, wherein the highlighting mode comprises any one of increasing the representation area, highlighting the representation area, adding a frame for the representation area and popping the representation area outwards for a preset distance.

When a cancel operation of the selected representation area is acquired, the representation area is restored to an original state, the cancel operation comprises at least one of separating a cursor from the representation area, clicking the selected representation area, clicking a cancel control and triggering the cancel operation by a right key, and closing a suspension popup window for displaying diagnostic instructions.

Optionally, in some embodiments, the selecting operation includes a first type of selecting operation and a second type of selecting operation, where the first type of selecting operation and the second type of selecting operation correspond to different operation modes. When a second selected operation triggered by the representation area on the abnormal cause distribution diagram is obtained, the diagnosis explanation of the abnormal cause is displayed in the diagnosis explanation area of the auxiliary diagnosis report.

The first selecting operation and the second selecting operation may be set according to actual application requirements, and are not limited herein. For example, the first selection operation may be one or more of a cursor movement to the representation area, a click operation on the representation area, a dwell time of the cursor in the representation area exceeding a predetermined time, and the second selection operation may be one or more of a click selection control, a right key trigger selection option, and the like.

Optionally, the selecting operation further includes a third type of selecting operation, and when the third selecting operation triggered based on the indication area on the abnormal cause distribution diagram is acquired, the diagnostic description of the abnormal cause corresponding to the indication area may be displayed in a popup window form according to the trigger position, and the diagnostic description of the abnormal cause may be displayed in a diagnostic description area of the auxiliary diagnostic report. In summary, by the abnormality cause distribution map, the user can select a diagnostic specification of the abnormality cause to be viewed by operating the cursor.

And the abnormality cause distribution table shows the respective abnormality causes and their diagnostic probabilities in the form of a table. The user can select the abnormality cause to be employed based on the abnormality cause distribution table. When a selected operation triggered based on the abnormality cause distribution table is acquired, a diagnosis specification of the abnormality cause is displayed in a diagnosis specification area of the auxiliary diagnosis report. That is, the diagnostic specification area is used to display a diagnostic specification of the cause of the abnormality employed.

When a deselect operation for the selected abnormality cause is acquired, the diagnosis specification area deletes the diagnosis specification of the abnormality cause of the diagnosis specification area.

In summary, by the abnormality cause distribution table, the user can select an abnormality cause to be employed by a selection operation of a cell of the abnormality cause, and display a diagnosis description of the abnormality cause in the diagnosis description area. Wherein, the diagnosis explanation of the abnormality cause is displayed in turn according to the time when the abnormality cause is selected.

Consider the situation where there may be an imperfection in the cause of the abnormality provided by the possible auxiliary diagnosis, e.g., a doctor determines the possible cause of the abnormality as a in combination with his own experience, but the cause of the abnormality provided by the auxiliary diagnosis does not include a. In this case, in the present embodiment, a supplement function for the cause of the abnormality may also be provided so that the cause of the abnormality can be manually supplemented by a person.

In one embodiment, the auxiliary diagnostic information processing method further comprises the steps of acquiring a supplementary abnormality cause and a diagnostic specification of the supplementary abnormality cause when the supplementary operation on the abnormality cause is acquired, adding the supplementary abnormality cause to an abnormality cause distribution chart and/or a table, and storing the diagnostic specification of the supplementary abnormality cause, wherein the diagnostic specification of the supplementary abnormality cause is displayed when triggered to be checked.

For the auxiliary diagnostic information, if the user needs to supplement the cause of the abnormality based on experience, the supplementary operation may be used for the supplement. Wherein the replenishment operation may be triggered based on an abnormality cause profile or an abnormality cause profile table.

In one embodiment, a supplemental control may be provided in the anomaly cause profile that, when triggered by a user, displays supplemental anomaly causes in the anomaly cause profile and/or anomaly cause distribution table.

In one embodiment, a supplemental control may be provided in the anomaly cause distribution table that, when triggered by a user, displays supplemental anomaly causes in the anomaly cause distribution map and/or anomaly cause distribution table. As shown in fig. 8, the supplemental control is the "add" control in the diagram, and after the addition is triggered, the custom popup window shown in fig. 9 is popped up, which guides the user to fill out the cause of the anomaly, and the diagnostic statement. When the user completes the filling, the supplementary abnormality cause is displayed in the abnormality cause distribution table shown in fig. 8.

And a diagnostic statement of the supplemental cause of the abnormality is displayed when the supplemental cause of the abnormality is selected. The display method of the diagnosis explanation of the abnormality cause and the selection method of the supplementary abnormality cause are the same as the processing method of other abnormality causes, and will not be described here.

As mentioned above, the auxiliary diagnostic system is obtained based on the test data of the test sample and the sample-related information, and the doctor can supplement the cause of the abnormality and the diagnostic description thereof based on experience. Both of these methods require accurate test data and sample related information as a basis. The sample related information may include sample information, clinical information of a sample provider, and custom parameters. The provision of auxiliary diagnostic information may be re-triggered when any of the sample information, the clinical information of the sample provider, and the custom parameters change.

In one embodiment, a sample information interface, a custom parameter interface, and a clinical information selection interface are provided. To facilitate user operation, three interfaces may be provided on one page, as shown in FIG. 10.

In another embodiment, the sample information interface, the custom parameter interface, and the clinical information selection interface may also be provided separately. Wherein, a sample information interface is provided, as shown in fig. 11, where a user can view and edit. The sample information may include basic information of the sample provider, such as age, gender, etc. The input of clinical symptoms can be triggered at the sample information interface. Clinical symptoms are more important for auxiliary diagnosis, different diseases can have different clinical manifestations, different clinical manifestations correspond to different diagnosis results, and doctors can select and input clinical information according to the clinical manifestations of sample providers. A clinical information selection interface for one embodiment is shown in fig. 12. The selected clinical symptoms will be shown in the lower selected symptom box and if a misselection is found, the selection can be deselected by a red cross in the upper right corner of the corresponding symptom. Wherein the selected state representing the abnormal information includes all abnormal information which is currently selected.

The custom parameters are a supplementary mode for non-system parameters provided by the system, and can be recorded in the data storage module as a necessary condition of diseases, the side of the knowledge graph can be specified, and the custom parameters can be used as one of the inputs as long as the knowledge graph has the custom parameters related to the recording. For example, some parameters required for auxiliary diagnosis are processed by a non-sample analyzer, but processed by other instruments, and at this time, can be recorded by means of custom parameters. In one embodiment, a custom parameter interface is also provided, so that a doctor can conveniently input custom parameters according to actual requirements.

In one embodiment, the method comprises the steps of updating sample information, clinical information and custom information in response to an edit operation of at least one of the sample information, the clinical information and the custom information triggered by a sample related information interface, and instructing an auxiliary diagnostic information providing device to update an auxiliary diagnostic report according to at least one of the updated sample information, the clinical information and/or the custom information in response to a report update operation, wherein the report update operation comprises at least one of a confirm operation for the edit operation and an update operation for the auxiliary diagnostic report.

For example, the method comprises the steps of acquiring editing and confirming operation of at least one of sample information, clinical information and custom information triggered based on a sample related information interface, and updating the auxiliary diagnosis report according to the updated sample information, clinical information and/or custom information indicated by the editing and confirming operation. In this embodiment, the auxiliary diagnostic report is updated when the user confirms the editing operation, such as saving the editing information.

The sample related information interfaces are the sample information interfaces, the clinical information selection interfaces and the custom parameter interfaces. When the user triggers the editing and confirming operation based on any one of the three interfaces, the auxiliary diagnosis report is updated according to the updated sample information, clinical information and/or custom information indicated by the editing and confirming operation, namely, the auxiliary diagnosis report is updated after the information is stored.

For another example, an edit and confirm operation for at least one of sample information, clinical information, and custom information triggered based on a sample related information interface is obtained, an information update prompt is triggered according to the sample information, clinical information, and/or custom information indicated to be updated by the edit and confirm operation, and an auxiliary diagnostic information providing device is instructed to update the auxiliary diagnostic report according to the updated sample information, clinical information, and/or custom information in response to a diagnostic update instruction triggered based on the information update prompt.

In this embodiment, when the user triggers editing and confirmation operations based on any one of the three interfaces, information update prompting is performed on the auxiliary diagnosis report interface. The information update prompt is used to prompt the user that the sample related information is modified, and possibly that the auxiliary diagnosis is changed. An updated as well as non-updated selection may be provided for selection by the user. When the user triggers the update option, an update indication is generated, the update indication being used to instruct the auxiliary diagnostic information providing apparatus to update the auxiliary diagnostic report according to the updated sample information, clinical information and/or custom information. That is, in this embodiment, after the sample related information is updated, the user is prompted to update the information, and the user selects whether to update the auxiliary diagnostic report.

In the present embodiment, the sample information, the clinical information and the custom information are updated through the sample related interface, so that accurate and perfect information can be ensured to be recorded. And after the information is updated, the update of the auxiliary diagnosis report is correspondingly triggered, so that the auxiliary diagnosis report is updated in time, and the accuracy of the auxiliary diagnosis report is ensured.

In one embodiment, the auxiliary diagnostic report includes an abnormality cause profile and/or table, and a diagnostic specification area. As described above, the diagnostic specification area is used to display a diagnostic specification of the cause of the abnormality employed. When the printing operation of the auxiliary diagnosis report is received, the auxiliary diagnosis report is printed, so that the user can know the auxiliary diagnosis content, the abnormality cause adopted by the doctor, and the abnormality specification of the abnormality cause from the auxiliary diagnosis report.

In one embodiment, a presentation priority of the selected abnormality causes is determined based on at least one of an order in which the abnormality causes are selected, a diagnosis probability of the abnormality causes, and a supplemental abnormality cause, a diagnostic specification of the selected abnormality causes is presented in order based on the presentation priority, a secondary diagnostic report is printed when a print operation of the secondary diagnostic report is received, the secondary diagnostic report including an abnormality cause distribution map and/or table, and a diagnostic specification area ordered in accordance with the presentation priority.

The display priority is used for determining the display sequence of the diagnosis instructions of the abnormal reasons in the diagnosis instruction area, and the higher the display priority is, the greater the possibility that the abnormal reasons cause sample abnormality is indicated from the view habit of a user. Therefore, by displaying the diagnosis description of the cause of the abnormality in the diagnosis description area with the display priority, the user can be presented with a degree of possibility of the cause of the abnormality.

In one embodiment, the presentation priority of the selected abnormality cause may be determined according to at least one of an order in which the abnormality causes are selected, a diagnosis probability of the abnormality cause, and a supplementary abnormality cause.

When the user operates the actual service, the user usually selects according to the possibility degree of the abnormality cause, for example, the user selects the abnormality cause considered to be most likely, and then selects some abnormality causes with low possibility. Therefore, the selected sequence of the abnormal reasons is considered, and the actual business operation habit of the user can be met.

In one embodiment, the diagnostic specification of the selected abnormality cause is presented in the diagnostic specification area in the order in which the abnormality causes are selected, and when a print operation of a secondary diagnostic report is received, the secondary diagnostic report is printed, the secondary diagnostic report including an abnormality cause profile and/or table, and the diagnostic specification area. In this embodiment, the diagnostic instructions for the abnormality causes in the auxiliary diagnostic report are printed in the order in which the abnormality causes are selected. When the actual business is operated, the user can determine the order of selecting the abnormal reasons according to the importance degree of the abnormal reasons.

In one embodiment, the diagnostic probability of an abnormality cause can indicate the degree of likelihood of the abnormality cause. Therefore, the degree of possibility of the abnormality cause can be expressed by considering the diagnosis probability of the abnormality cause.

In one embodiment, when the abnormality cause is selected, a presentation priority is determined according to a diagnosis probability of the abnormality cause, the higher the diagnosis probability, the greater the presentation priority, a sorting presentation of the diagnosis instructions of the abnormality cause that has been selected according to the presentation priority, when a printing operation of a secondary diagnosis report is received, the secondary diagnosis report including an abnormality cause distribution map and/or table, and the diagnosis instruction area is printed. In this embodiment, the diagnostic instructions of the selected abnormal cause are displayed in order according to the order of the diagnostic probabilities of the selected abnormal cause, so as to assist in the printing of the diagnostic probabilities of the diagnostic instructions of the abnormal cause in the diagnostic report.

In another implementation, when a supplemental abnormality cause is added by a user and selected, the likelihood of a possible supplemental abnormality cause is highest, and therefore, when the supplemental abnormality cause is selected, the supplemental abnormality cause is determined as the highest presentation priority, diagnostic instructions of the abnormality cause that have been selected are presented in order according to the presentation priority, and when a print operation of an auxiliary diagnostic report is received, the auxiliary diagnostic report is printed, the auxiliary diagnostic report including an abnormality cause distribution map and/or table, and the diagnostic instruction area. In this embodiment, the selected additional abnormality causes have the highest display priority, and other selected abnormality causes may be displayed in order of the selected time or in order of the diagnostic probability. In another embodiment, the auxiliary diagnostic report may be printed along with the analysis report of the sample analyzer.

In another embodiment, the interface for aiding in diagnostic reporting is shown in FIG. 13, and includes an abnormality cause profile, an abnormality cause profile table, an operation area, a diagnostic specification area, other abnormality areas, and a prompt information area.

The abnormal reason distribution map is used for displaying auxiliary diagnosis results of the corresponding samples. In one embodiment, the first N abnormality causes with the greatest diagnostic probability are displayed. The distribution diagram is shown in a Nannbuguer rose pattern mode, the center is a blank circle, the periphery is a sector with different colors in equal radian, each sector is provided with a lead, the other end of the lead is an abnormal cause and diagnosis probability, the diagnosis probability is in a square bracket behind the abnormal cause in a percentage mode, the radius of the sector is related to the diagnosis probability, and the larger the probability is, the longer the radius is, and the shorter the opposite is.

The abnormal cause distribution table is divided into a left table and a right table, each table is provided with 3 columns of printing, abnormal cause and diagnosis probability, each table except the table head is provided with 6 rows, the analyzed diagnosis result can be filled with a left list firstly, and the left list is filled with a right list later. The first column of the table is a check box, the second column is an abnormality cause, the third column is a probability of diagnosing a disease, and the probability is percentage data with two decimal places.

The diagnostic specification area is used for displaying diagnostic specification of the abnormality cause selected in the abnormality cause distribution table, and is capable of automatically displaying a scroll bar according to how much content is, when the content exceeds the lower boundary of the area, the right side will automatically display the scroll bar, and clicking the scroll bar to move a mouse or scrolling using a mouse wheel will scroll up and down to display the content. The contents of the diagnostic specification area cannot be edited or modified, and only the contents can be added or removed by a selected operation of the abnormality cause distribution table.

The operation area has 3 buttons for adding, modifying and deleting.

When the abnormality cause distribution table has abnormality cause information, only one abnormality cause is in a selected state at any time, when the abnormality cause analyzed by the auxiliary diagnosis system is selected, the modification and deletion operation buttons are in a disabled state, modification of the abnormality cause diagnosed by the system is not allowed, and when the abnormality cause supplemented by the medicine is selected, the modification and deletion operation buttons are in an enabled state, so that a doctor is allowed to modify or delete the supplemented abnormality cause.

When the number of the abnormal reasons is less than 12, the adding button is in an activated state, a doctor can supplement the abnormal reasons, when the number of the abnormal reasons is over 12, the adding button is disabled, the continuous supplement of the abnormal reasons is forbidden, when the number of the abnormal reasons is over 12, the abnormal reasons need to be added again, only one of the supplemented abnormal reasons can be deleted first, and then the abnormal reasons can be added.

Other possible abnormality cause areas, the diagnosis results analyzed by auxiliary diagnosis, besides the first N abnormality causes, also have other abnormality causes with smaller possibility, and the abnormality causes display the possible abnormality cause areas.

In another embodiment, the auxiliary diagnostic information providing apparatus, as shown in fig. 14, includes a data processing module 1301, an auxiliary diagnostic analysis module 1302, and an auxiliary diagnostic report output module 1303.

Specifically, the data processing module 1301 is configured to obtain test data of a sample to be tested, and pre-process the test data to obtain information to be diagnosed.

It should be noted that the sample to be tested is a sample obtained from a sample provider body and containing various biological cell information or other biological information, and the corresponding test data is corresponding analysis data obtained by counting and testing various biological samples containing biological cell information or other biological information, for example, the test data may be blood routine test information, such as abnormal cell type, cell number characteristics, cell size characteristics, cell composition proportion characteristics, cell content characteristics, nucleic acid content characteristics and the like contained in blood.

The information to be diagnosed comprises at least one of items to be tested, numerical information corresponding to the items to be tested and basic information corresponding to samples to be tested.

By way of example, taking the test data as a cell number feature, the items to be tested may be neutrophil number, neutrophil percentage, eosinophil number, eosinophil percentage, monocyte number, monocyte percentage, white blood cell number, erythrocyte percentage, etc., and the basic information corresponding to the sample to be tested is age, species, sex, etc. of the sample provider to which the sample to be tested belongs.

The obtaining of the test data of the sample to be tested may mean that the test data obtained by performing test analysis on the sample to be tested by the sample analyzer is imported from the sample analyzer through communication connection with the sample analyzer.

In some alternative embodiments, the numerical information corresponding to the item to be inspected may be converted into an ascending and descending of the index thereof according to the normal range of the corresponding item of the corresponding species.

In an embodiment of the present application, the data processing module 1301 converts the structured test data into data to be diagnosed as input to the auxiliary diagnostic analysis module 1302. Specifically, the data processing module 301 converts all the test items, and the program outputs all the knowledge as a temporary intermediate file, where each line in the temporary intermediate file is a single converted test item result, and the test item result content includes a sample number, a species name, a test package name, a test item chinese name, a test item english name, a test index floating condition, a floating percentage, a test item value, and the like.

It should be noted that, the test package name, the test item chinese name and the test item english name acquired by different instruments and hospitals may be different, and the embodiment of the present application is not limited to the above.

The auxiliary diagnosis analysis module 1302 is configured to obtain the information to be diagnosed obtained by the data processing module 1301, and obtain a target knowledge graph, so as to match the information to be diagnosed with the target knowledge graph, so as to obtain a matching result.

Specifically, during the matching process, the auxiliary diagnosis analysis module 1302 matches the information to be diagnosed from the data processing module 1301 with the target knowledge graph according to the direction indicated by the edge in the target knowledge graph, so as to count the frequency of occurrence of each abnormal cause, determine a candidate list of the abnormal cause according to the frequency of occurrence of each abnormal cause, and determine the next examination and treatment information based on the candidate list of the abnormal cause.

The target knowledge graph may be a knowledge graph formed by information such as a test item of a sample provider, a subsequent examination of an abnormality cause, a treatment scheme, and the like, and different test categories may correspond to different knowledge graphs.

In an alternative embodiment, after the auxiliary diagnosis analysis module 302 obtains the information to be diagnosed of the data processing module 301, the auxiliary diagnosis analysis module obtains the target knowledge graph corresponding to the test item according to the test category corresponding to the information to be diagnosed. By way of example, taking the conventional diagnosis of animal blood as the current test item, the sources of the target knowledge patterns include medical guideline documents of various disease differential diagnosis guidelines, such as "small animal medical differential diagnosis", "laboratory test for pet diseases and diagnosis color pattern and additional case analysis", etc.

Fig. 15 is a schematic diagram of a target knowledge graph according to an embodiment of the present application. As shown in fig. 15, the target knowledge-graph includes nodes and directed edges connecting the nodes.

The nodes are of two types, one is used for representing abnormal information nodes obtained from various medical guidelines, the abnormal information nodes contain information such as follow-up examination, treatment schemes and the like of various abnormal reasons, and the other is used for representing clinically seen nodes which are the ascending/descending of various indexes of examination, such as leucocyte ascending and the like.

It should be noted that, the names of the nodes in the target knowledge graph are unique, and the names of the edges are result prompts to represent the relationships among the nodes of different types. The direction of the edge indicates the order of precedence between two nodes connected (i.e., clinically seen nodes, abnormal information nodes), the number of occurrences of the current clinically seen and abnormal information in how many documents the edge contains, and the connection weight of the nodes (e.g., the connection initial weight may be set to 1).

Fig. 16 is a schematic diagram of a target knowledge graph corresponding to an abnormality cause of suppurative inflammation diseases according to an embodiment of the present application. As shown in FIG. 16, clinical findings corresponding to suppurative inflammatory diseases include increase in neutrophil count, increase in neutrophil percentage, increase in eosinophil count, increase in eosinophil percentage, increase in monocyte count, increase in monocyte percentage, increase in leukocyte count, and increase in erythrocyte percentage.

In the matching process, when any one or more of the above clinical findings are presented in the data to be diagnosed, the abnormality cause pointed to is 'suppurative inflammation'.

The auxiliary diagnosis information providing device in the embodiment of the application adopts the knowledge graph to match the information to be diagnosed to obtain the matching result, then outputs auxiliary diagnosis and reports according to the matching result, compared with human analysis, the knowledge range covered by the knowledge graph involved in the device is wider, so that the subjective factor influence of medical staff can be avoided, key information can be rapidly extracted, deep analysis and accurate judgment can be performed, and the efficiency and the accuracy can be ensured.

In addition, it should be noted that the knowledge graph can be dynamically expanded according to actual requirements to update nodes and relationships. For example, when new blood routine knowledge about suppurative inflammation exists, the new knowledge is added to the knowledge graph or the original knowledge is modified, so that medical staff can acquire the new blood routine knowledge in time in clinical work, and provide standardized examination and treatment for patients suffering from suppurative inflammation according to the latest diagnosis and treatment scheme according to actual conditions.

Further, after obtaining the information to be diagnosed, the auxiliary diagnosis analysis module 1302 may perform matching in the target knowledge graph according to the similarity between the texts, the euclidean distance between the text vectors, and the like, so as to obtain the relationship between the clinically seen and abnormal information in the knowledge graph.

In a specific implementation, all anomalies corresponding to the knowledge can be found in the target knowledge graph by the following formula:

Where K is the edge of the anomaly information and the test item, and s= { a ₁,a₂,...a_n } is the set of test items.

Specifically, the auxiliary diagnosis analysis module 1302 obtains information to be diagnosed according to the temporary intermediate file of the data processing module 1301, matches an abnormal cause corresponding to the information to be diagnosed in the target knowledge graph from the item to be tested and/or numerical information corresponding to the item to be tested indicated in the information to be diagnosed, and obtains a first occurrence frequency of at least one abnormal cause corresponding to the sample to be tested according to the matching result, where the first occurrence frequency is used to indicate the occurrence times of the correspondence between the clinical findings of the abnormal cause and the abnormal information in the literature corresponding to the target knowledge graph.

The auxiliary diagnosis analysis module 1302 will repeat the above steps until the combination of the names of the inspection items and the floating conditions of the inspection items in the target knowledge graph is completely traversed, and finally, the first occurrence frequency of at least one abnormal cause corresponding to the sample to be inspected in the target knowledge graph is obtained through statistics.

It should be noted that, after the first occurrence frequency of each abnormality cause is obtained, the same frequency of multiple abnormality causes may occur, and the greater the weight of one clinically seen and abnormality information relationship in the more guideline documents to describe this knowledge. Therefore, when the frequencies of the corresponding abnormality causes seen clinically are the same, it is also possible to rank according to the frequencies of the clinically seen and abnormality information in different documents.

Specifically, the auxiliary diagnostic analysis module 1302 is further configured to obtain a second occurrence frequency of the at least two abnormal reasons corresponding to the sample to be tested in the preset document when the first occurrence frequencies of the at least two abnormal reasons are the same, and according to the first occurrence frequency and the second occurrence frequency, the first abnormal reason and the probability corresponding to each first abnormal reason.

The embodiment of the present application is not particularly limited to the preset document. For example, different information to be diagnosed corresponds to different preset document sets, and preset documents to be searched can be determined according to the information to be diagnosed.

For example, after matching by the target knowledge graph, the first occurrence frequencies of the abnormality cause a, the abnormality cause B, and the abnormality cause C are all X times, and the preset documents corresponding to the information to be diagnosed can be found as document 1, document 2, and document 3. At this time, the total occurrence times of the abnormality cause A, the abnormality cause B and the abnormality cause C in 3 documents are searched respectively and counted as second occurrence frequency, and if the second occurrence frequency of the abnormality cause A is larger than the second outgoing line frequency of the abnormality cause B and the second occurrence frequency of the abnormality cause C is larger than the second outgoing line frequency of the abnormality cause A, the target abnormality information is obtained that the probability of the abnormality cause C is higher than the abnormality cause A and the probability of the abnormality cause A is higher than the abnormality cause B.

In some optional embodiments, after obtaining the first occurrence frequency of each abnormal cause, the auxiliary diagnostic analysis module 1302 may further sort at least one abnormal cause according to the first occurrence frequency of at least one abnormal cause corresponding to the sample to be tested, so as to quickly determine, according to the sorting result, the abnormal causes with the same occurrence frequency in the sample to be tested, so as to improve the efficiency of determining the abnormal cause with the same occurrence frequency.

In some alternative embodiments, the auxiliary diagnostic analysis module 1302 is further configured to determine a probability that the occurrence frequency meets a first preset requirement and corresponds to a first abnormality cause.

Specifically, for the specific content of the first abnormality cause satisfying the first preset requirement, the embodiment of the present application is not limited, and may be set as "the first abnormality cause having the first occurrence frequency greater than N ₁" for the first abnormality cause "or may be set as" the first abnormality cause having the first occurrence frequency of M ₁ "before ranking for the first abnormality cause".

Further, the auxiliary diagnostic analysis module 1302 is further configured to determine, according to the probabilities, a second abnormality cause of the first abnormality cause for which the probabilities satisfy a second preset requirement.

Similarly, for the specific content of the second abnormality cause satisfying the second preset requirement, the embodiment of the present application is not limited, and may be set as "the abnormality cause with the second occurrence frequency greater than N ₂" for the second abnormality cause "or may be set as" the abnormality cause with the second occurrence frequency M ₂ "before ranking for the second abnormality cause".

Further, after obtaining the probability corresponding to the second abnormal cause, the auxiliary diagnosis report output module 303 is further configured to obtain an auxiliary diagnosis rose according to the probability corresponding to the second abnormal cause, where the auxiliary diagnosis rose includes sector areas corresponding to the abnormal causes, respectively.

The first occurrence frequency, probability height, directed edge number and the like of the abnormal reasons are displayed by at least one of radius length, circle center angle and region color of the fan-shaped region, and specific contents of the auxiliary diagnosis rose are shown in the following embodiments.

Fig. 17 is a schematic structural diagram of data to be diagnosed according to an embodiment of the present application. It should be noted that, after receiving the test data, the data processing module 1301 converts the test data into a knowledge display manner as shown in fig. 17, and in the auxiliary diagnostic report output module, this content is also used as a "test visible" portion and is embedded in the visualized auxiliary diagnostic report.

In some embodiments, the auxiliary diagnostic report includes at least one of anomaly information corresponding to the sample to be tested, an auxiliary diagnostic radar map for indicating the cause of the anomaly corresponding to the sample provider and probabilities corresponding to the respective causes of the anomaly, an anomaly population distribution map, and historical anomaly information for the sample provider.

Fig. 18 is an exemplary auxiliary diagnostic rose provided by an embodiment of the present application. As shown in fig. 18 (a), the auxiliary diagnostic radar rose includes sector areas corresponding to the reasons of the abnormality one by one, and the user can clearly see the reasons of the abnormality corresponding to the sample to be inspected in the auxiliary diagnostic radar.

In one specific implementation, the fan-shaped region displays the first occurrence frequency, the probability height and the number of directed edges of the abnormal reason through at least one of the radius length, the circle center angle and the region color.

As shown in fig. 18, the first occurrence frequency corresponding to the abnormal cause type, that is, the relation between the clinical findings corresponding to each abnormal cause and the abnormal information, may be indicated by the radius of the sector, the probability of each abnormal cause may be indicated by the color of the sector, and the number of directional edges of each abnormal cause in the target knowledge graph may be indicated by the central angle degree of the sector, wherein the number of directional edges is used to indicate the number of clinical findings corresponding to each abnormal cause in the target knowledge graph.

Further, when a selection operation based on a trigger is performed, a diagnostic specification of the cause of the abnormality selected is displayed. Referring to fig. 18 (a) and (b), when the cursor of the mouse hovers over a sector area of "blood/bone marrow abnormality or tumor", the diagnostic description of the cause of the abnormality corresponding to the sector area is popped up. Fig. 18 is only an exemplary illustration, and is not limited to this in practical application.

The terminal to which the auxiliary diagnostic information processing apparatus is applied should have a display function, for example, a smart phone, a personal computer, a medical diagnostic instrument, or if a sample analyzer integrated with the auxiliary diagnostic information providing apparatus has a display function, an auxiliary diagnostic report may be displayed by the sample analyzer.

In this embodiment, the diagnosis information providing system is a medical auxiliary diagnosis device that integrates a biological sample analysis and a visual diagnosis test report output, in which the biological sample analysis is performed to obtain test data by performing a detection analysis on the biological sample, and the diagnosis data is processed to obtain data to be diagnosed. The diagnosis information providing system may be, for example, a blood analysis system, which may be obtained by upgrading a blood analyzer, and includes a sampling component, a reaction component, a driving component and a detection component for detecting and analyzing a blood sample to obtain sample detection data, where the auxiliary diagnosis information providing device may be stored in a memory of the blood analysis system as a computer program product for implementing an auxiliary diagnosis function based on a computer program flow, and the auxiliary diagnosis function of the auxiliary diagnosis information providing device implementing an embodiment of the present application is executed by a processor. The auxiliary diagnosis information processing apparatus can be stored in a memory of a blood analysis system as a computer program product for realizing an auxiliary diagnosis function based on a computer program flow, and the steps of the auxiliary diagnosis information processing method according to the embodiment of the application are executed by a processor.

In the above embodiments, it should be understood that the disclosed apparatus and its implementation may be implemented in other manners. For example, the above-described device embodiments are merely illustrative, e.g., the division of modules is merely a logical function division, and there may be additional divisions of actual implementation, e.g., multiple modules may be combined or integrated into another system, or some features may be omitted or not performed.

Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms. In addition, each functional module in the embodiments of the present application may be integrated in one processing unit, or each module may exist alone physically, or two or more modules may be integrated in one unit. The units formed by the modules can be realized in a form of hardware or a form of hardware and software functional units.

The integrated modules, which are implemented in the form of software functional modules, may be stored in a computer readable storage medium. The software functional modules described above are stored in a storage medium and include instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform some steps of the methods of the various embodiments of the application.

The storage medium may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk, and the like. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.

Claims

1. A method of processing auxiliary diagnostic information, comprising:

2. The method of claim 1, wherein the anomaly cause profile includes a respective anomaly cause correspondence representation area;

The method includes displaying a diagnostic specification of the abnormality cause selected when a selected operation triggered based on the abnormality cause profile/table is acquired, including at least one of:

The first method comprises the steps of displaying a diagnosis description of an abnormal cause corresponding to a representation area in a popup window mode according to a triggering position when a selected operation triggered based on the representation area on the abnormal cause distribution diagram is obtained, wherein the selected operation comprises at least one of cursor movement to the representation area, clicking operation on the representation area, clicking a selection control when the stay time of the cursor in the representation area exceeds a preset time, and right-click triggering selection options;

And secondly, when a selected operation triggered based on a representation area on the abnormal cause distribution diagram is acquired, displaying a diagnosis description of the abnormal cause in a diagnosis description area of the auxiliary diagnosis report, wherein the diagnosis description area is arranged below the abnormal cause distribution diagram, the selected operation comprises at least one of cursor moving to the representation area, clicking operation on the representation area, clicking a selection control when the stay time of the cursor in the representation area exceeds a preset time, and right-click triggering a selection option.

3. The method according to claim 2, wherein the method further comprises:

When a selected operation triggered by a representation area on the abnormal cause distribution diagram is acquired, the selected representation area is switched from an original state to a highlighting state, wherein the highlighting mode comprises any one of increasing the representation area, highlighting the representation area, increasing a frame for the representation area and popping the representation area outwards for a preset distance.

4. A method according to claim 3, characterized in that the method further comprises:

When a cancel operation of the selected representation area is acquired, the representation area is restored to an original state, wherein the cancel operation comprises at least one of separating a cursor from the representation area, clicking a cancel control and triggering a cancel selection option by a right key;

And canceling to display the diagnosis description of the abnormality cause corresponding to the representation area.

5. The method according to claim 1 or 2, wherein the anomaly causes of the anomaly cause distribution table are arranged in order of probability;

The method comprises the steps of firstly, displaying a diagnosis description of an abnormal reason corresponding to a cell in a popup window mode according to a triggering position when a selected operation of the cell triggered based on the abnormal reason distribution table is obtained, wherein the selected operation comprises at least one of moving a cursor to the cell of the abnormal reason, clicking a selection control of the abnormal reason when the stay time of the cursor in the cell of the abnormal reason exceeds a preset time, and triggering a right key to select options;

And secondly, when a selection operation of the cell triggered based on the abnormal reason distribution table is obtained, displaying a diagnosis description of the abnormal reason corresponding to the cell in the diagnosis description area, wherein the selection operation comprises a cursor moving to the cell of the abnormal reason, a clicking operation of the cell of the abnormal reason, a stay time of the cursor in the cell of the abnormal reason exceeding a preset time, clicking a selection control of the abnormal reason, and triggering at least one of selection options by a right key, wherein the diagnosis description area is arranged below the abnormal reason distribution table.

6. The method of claim 2, wherein the anomaly cause profile is further used to indicate a number of directed edges corresponding to the sample to be inspected and a frequency of occurrence corresponding to the anomaly cause;

The occurrence frequency of the abnormal reasons is used for indicating the occurrence times of the corresponding relation between the clinical findings of the abnormal reasons and the abnormal information in the literature corresponding to the target knowledge graph;

The abnormality cause distribution map includes any one of a pie chart, a radar chart, and a chord chart, and the abnormality cause distribution map shows the probability of the abnormality cause, the number of directed edges, and the occurrence frequency of the abnormality cause by at least one of an area, an angle, a color, and a shape.

7. The method according to claim 1, wherein the method further comprises:

When a supplementary operation for the abnormality cause is acquired, acquiring a supplementary abnormality cause and a diagnostic specification of the supplementary abnormality cause;

Adding the supplemental abnormality cause to the abnormality cause profile and/or table and storing a diagnostic specification of the supplemental abnormality cause, the diagnostic specification of the supplemental abnormality cause being displayed when the supplemental abnormality cause is selected.

8. The method according to claim 2, 5 or 7, characterized in that the method:

determining the display priority of the selected abnormal reasons according to at least one of the selected order of the abnormal reasons, the diagnosis probability of the abnormal reasons and the supplementary abnormal reasons;

sorting and displaying the diagnosis description of the abnormal reasons selected according to the display priority;

When a print operation of an auxiliary diagnostic report is received, the auxiliary diagnostic report is printed, the auxiliary diagnostic report including an abnormality cause profile and/or table, and the diagnostic specification areas ordered by presentation priority.

9. The method according to claim 1, wherein the method further comprises:

updating the sample information, the clinical information and the custom information in response to an editing operation of at least one of the sample information, the clinical information and the custom information triggered by a sample related information interface;

In response to a report update operation, instruct the auxiliary diagnostic information providing apparatus to update the auxiliary diagnostic report according to at least one of updated sample information, clinical information, and/or custom information;

wherein the report update operation includes at least one of a confirmation operation for the editing operation, and an update operation for the auxiliary diagnostic report.

10. An auxiliary diagnostic system, comprising:

A processing apparatus for auxiliary diagnostic information, which realizes the steps of the method for processing auxiliary diagnostic information according to any one of claims 1 to 9.