CN118782266B - Funnel-type medical data insight system, method, medium, program product and terminal - Google Patents
Funnel-type medical data insight system, method, medium, program product and terminal Download PDFInfo
- Publication number
- CN118782266B CN118782266B CN202411276465.XA CN202411276465A CN118782266B CN 118782266 B CN118782266 B CN 118782266B CN 202411276465 A CN202411276465 A CN 202411276465A CN 118782266 B CN118782266 B CN 118782266B
- Authority
- CN
- China
- Prior art keywords
- insight
- search
- condition
- layer
- medical data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 80
- 238000011160 research Methods 0.000 claims abstract description 25
- 230000008569 process Effects 0.000 claims abstract description 18
- 238000010835 comparative analysis Methods 0.000 claims abstract description 8
- 238000004590 computer program Methods 0.000 claims description 18
- 238000004458 analytical method Methods 0.000 claims description 16
- 201000010099 disease Diseases 0.000 claims description 13
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 13
- 238000011282 treatment Methods 0.000 claims description 7
- 238000007670 refining Methods 0.000 claims description 5
- 230000009471 action Effects 0.000 claims description 4
- 230000006870 function Effects 0.000 description 12
- 238000010586 diagram Methods 0.000 description 10
- 229940079593 drug Drugs 0.000 description 5
- 239000003814 drug Substances 0.000 description 5
- 230000000694 effects Effects 0.000 description 5
- 208000001910 Ventricular Heart Septal Defects Diseases 0.000 description 4
- 238000013461 design Methods 0.000 description 4
- 238000003745 diagnosis Methods 0.000 description 4
- 208000002330 Congenital Heart Defects Diseases 0.000 description 3
- 210000004369 blood Anatomy 0.000 description 3
- 239000008280 blood Substances 0.000 description 3
- 210000004027 cell Anatomy 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 208000028831 congenital heart disease Diseases 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 230000003068 static effect Effects 0.000 description 3
- 201000003130 ventricular septal defect Diseases 0.000 description 3
- 235000019800 disodium phosphate Nutrition 0.000 description 2
- 238000002651 drug therapy Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000002074 nanoribbon Substances 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000001356 surgical procedure Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004820 blood count Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000007717 exclusion Effects 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 210000000265 leukocyte Anatomy 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000004549 pulsed laser deposition Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000011269 treatment regimen Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Data Mining & Analysis (AREA)
- Biomedical Technology (AREA)
- Databases & Information Systems (AREA)
- Pathology (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
本申请提供漏斗式医疗数据洞察系统、方法、介质、程序产品及终端，本发明支持分层式对医疗数据进行纳排，且每一层检索条件层均支持完整的变量检索功能，各层检索条件层不断细化数据范围得到最终的纳排条件；本发明为了在研究过程中帮助研究人员核对数据质量和研究方向，支持灵活查看各个检索条件层的患者概览信息、关注的变量填充率信息以及变量的值域分布和数据质量等检索结果信息，研究人员通过可视化的报表和数据概览信息，可以便捷地确认和不断优化探索条件以及方向；本发明还支持对多个洞察组进行对比分析，以获得效果更好的纳排条件，为研究人员进行后续研究提供了帮助。
The present application provides a funnel-type medical data insight system, method, medium, program product and terminal. The present invention supports hierarchical sorting of medical data, and each retrieval condition layer supports a complete variable retrieval function. Each retrieval condition layer continuously refines the data range to obtain the final sorting condition. In order to help researchers check data quality and research direction during the research process, the present invention supports flexible viewing of patient overview information, variable fill rate information of concern, and variable value domain distribution and data quality and other retrieval result information of each retrieval condition layer. Researchers can easily confirm and continuously optimize exploration conditions and directions through visualized reports and data overview information. The present invention also supports comparative analysis of multiple insight groups to obtain better sorting conditions, which provides assistance for researchers to conduct subsequent research.
Description
Technical Field
The application relates to the technical field of medical data, and more particularly to funnel-type medical data insight systems, methods, media, program products, and terminals.
Background
In the medical research field, clinicians and researchers face a series of challenges after determining the direction of the study, which often involve assessment of the nanodrainage conditions, data sample size, and data quality of the study design. This process requires not only intensive expertise, but also efficient data acquisition and analysis capabilities. In particular, in the initial stages of the study, extensive exploration is required to determine the appropriate inclusion and exclusion criteria (nanobars), a process that is critical to ensure the scientificity and effectiveness of the study. But currently there are the following difficulties:
(1) Scientific and understanding capabilities differ significantly in that different researchers have different degrees of difficulty in determining the nanoribbon conditions and evaluating the data sample size.
(2) The limitation of the data acquisition mode is that part of scientific researchers can directly inquire the required data from the professional database, and part of scientific researchers can only search the data by means of a third party platform. These platforms are typically oriented towards customers with clear scientific needs and data conditions, and may not be sufficiently convenient and applicable for researchers at the preliminary exploration stage.
(3) The limitations of data retrieval platforms are that most existing data retrieval platforms fail to adequately account for the exploratory needs of researchers at the beginning of a study, resulting in a lack of effective tools and methods for researchers in determining the nanoribbon conditions.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the present invention provides a funnel-type medical data insight system, method, medium, program product and terminal, for solving the problem that most researchers in the prior art lack a method for conveniently, rapidly and accurately exploring the nano-array condition.
To achieve the above and other related objects, a first aspect of the present application provides a funnel-type medical data insight system, which includes a configuration module configured to configure one or more insight groups according to user insight requirements, a search module connected to the configuration module, and configured to search medical data by using a funnel-type search method based on each of the insight groups to obtain a nanorow condition and a search result corresponding to each of the insight groups, and a comparison analysis module connected to the search module, and configured to compare and analyze the search result of each of the insight groups to obtain an optimal insight group and a nanorow condition corresponding to the optimal insight group meeting the user insight requirements.
In some embodiments of the first aspect of the present application, the process of searching the medical data by using a funnel search method based on each of the insight groups to obtain the nano-rank condition and the search result corresponding to each of the insight groups includes, for any of the insight groups, gradually refining the search condition by using the funnel search method to obtain a plurality of search condition layers of the insight group, each of the search condition layers having a sequential inclusion relationship, wherein a last search condition layer obtained after gradually refining the search condition of the insight group is the nano-rank condition of the current insight group, and the search result corresponding to the nano-rank condition is the search result of the current insight group.
In some embodiments of the first aspect of the present application, a query statement is generated according to a search condition of the current search condition layer, so as to perform query search on medical data according to the query statement.
In some embodiments of the first aspect of the present application, the plurality of search condition layers of each insight group search the medical data based on the search conditions of the current search condition layer, respectively, to obtain corresponding search results.
In some embodiments of the first aspect of the present application, the system further includes a result display module, where the result display module is configured to visually display the search result according to an observation index set by a user.
In some embodiments of the first aspect of the present application, the result display module may be further configured to visually display results of the comparative analysis of the plurality of insight groups.
To achieve the above and other related objects, a second aspect of the present application provides a method for funnel-type medical data insight, which is applied to the funnel-type medical data insight system, the method includes configuring one or more insight groups according to user insight requirements, searching medical data by a funnel-type search method based on each of the insight groups to obtain a corresponding nano-rank condition and a search result of each of the insight groups, and comparing and analyzing the search result of each of the insight groups to obtain an optimal insight group and a corresponding nano-rank condition according to the user insight requirements.
To achieve the above and other related objects, a third aspect of the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the funnel medical data insight method.
To achieve the above and other related objects, a fourth aspect of the present application provides a computer program product comprising computer program code for causing a computer to implement the funnel medical data insight method when the computer program code is run on the computer.
To achieve the above and other related objects, a fifth aspect of the present application provides an electronic terminal, including a memory, a processor, and a computer program stored on the memory, the processor executing the computer program to implement the funnel-type medical data insight method.
As described above, the funnel-type medical data insight system, method, medium, program product and terminal provided by the application have the following beneficial effects:
(1) According to the funnel type medical data insight system provided by the invention, layering is supported to carry out nano-ranking on medical data, each layer of retrieval condition layer supports a complete variable retrieval function, and each layer of retrieval condition layer continuously refines the data range to obtain a final nano-ranking condition;
(2) In order to help researchers check data quality and research direction in the research process, the invention supports to flexibly check the patient overview information of each search condition layer, the concerned variable filling rate information, the value range distribution of the variables, the data quality and other search result information, and the researchers can conveniently confirm and continuously optimize the exploration conditions and direction through the visualized report and the data overview information;
(3) The invention also supports the comparative analysis of a plurality of insight groups so as to obtain the nano-array condition with better effect, thereby providing assistance for researchers to carry out subsequent researches.
Drawings
Fig. 1 is a schematic flow chart of a funnel-type medical data insight method according to an embodiment of the present application.
FIG. 2 is a diagram illustrating a method for funnel-type medical data insight according to an embodiment of the present application.
FIG. 3 is a schematic diagram of a set of configuration insights in an embodiment of the present application.
FIG. 4 is a diagram of a search condition layer configured for each layer in an embodiment of the application.
Fig. 5 is a schematic diagram of a search result visualization according to an embodiment of the application.
FIG. 6 is a diagram illustrating the selection of an observation index according to an embodiment of the application.
FIG. 7 is a schematic diagram of a comparative analysis of multiple insight groups according to an embodiment of the present application.
Fig. 8 is a flowchart of a funnel-type medical data insight method according to an embodiment of the present application.
Fig. 9 is a schematic structural diagram of an electronic terminal according to an embodiment of the application.
Detailed Description
Other advantages and effects of the present application will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present application with reference to specific examples. The application may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
To facilitate an understanding of embodiments of the present application, a detailed description is first provided with reference to fig. 1. FIG. 1 illustrates a schematic diagram of a funnel-type medical data insight system in accordance with an embodiment of the present application. The structure of the funnel-type medical data insight system in this embodiment includes a configuration module 110, a retrieval module 120, and a contrast analysis module 130.
In one embodiment, the configuration module 110 is configured to configure one or more insight groups according to user insight requirements.
It should be noted that, in the configuration module 110 in the funnel-type medical data insight system, different insight groups are configured according to user insight requirements, such as research requirements of scientific researchers on medical data. Aiming at any disease research requirement of scientific researchers, corresponding insight groups, such as a disease drug treatment means insight group, a disease operation treatment means insight group and the like, can be configured based on different treatment schemes of diseases. In this embodiment, the number of insight groups is at most three.
In an embodiment, the retrieving module 120 is connected to the configuration module 110, and is configured to retrieve the medical data by adopting a funnel type retrieving method based on each of the insight groups, so as to obtain the nano-array condition and the retrieving result corresponding to each of the insight groups. On the foreground page of the funnel-type medical data insight system, the search module 120 configures search conditions based on each insight group, and a funnel-type search method is adopted as a search mode.
In some examples, retrieving medical data using a funnel retrieval method based on each of the insight groups to obtain a nanobar condition and a retrieval result corresponding to each of the insight groups includes:
for any insight group, adopting a funnel type searching method to gradually refine searching conditions so as to obtain a plurality of searching condition layers of the insight group, wherein each searching condition layer has a sequential inclusion relation;
The last layer of search condition layer obtained after the search conditions are gradually refined by the insight group is the nano-row condition of the current insight group, and the search result corresponding to the nano-row condition is the search result of the current insight group.
In some examples, the plurality of search condition layers of each insight group search the medical data based on search conditions of the current search condition layer, respectively, to obtain corresponding search results. And searching each layer of search condition layer of each insight group respectively, so that a search result of each layer of search condition layer can be obtained.
In some examples, a query statement is generated according to a search condition of a current search condition layer to query and search medical data according to the query statement. And analyzing according to the retrieval conditions of each retrieval condition layer to generate a query statement, and carrying out retrieval query in the medical data set by using the query statement.
It should be noted that, for any insight group, such as an insight group of a disease drug treatment means, a funnel-type search method is adopted to gradually refine the search conditions, search conditions are hierarchically configured on a foreground page to obtain each search condition layer, then the search conditions of each search condition layer are analyzed according to the corresponding combination mode to generate a query sentence, each search condition layer is hierarchically searched, and the search result of each search condition layer, including the sample size and the associated key, is stored.
Specifically, first-layer search condition layers are determined, variables contained in first-layer search conditions are read, relational characters between the variables and value fields are analyzed, if query sentences between the generated variables and the value fields are contained, larger than or not equal to null and the like, searching is performed in the whole data set range to obtain sample sizes and association keys (such as patient IDs, visit IDs and the like) which meet the search conditions.
Further, the user can dynamically adjust AND configure the search conditions, evaluate the search effect on each current search condition layer, if the search result of the current search condition layer does NOT meet the expectations, further refine AND set the search conditions, for example, refine the search conditions gradually on the basis of the first search condition layer to obtain the next search condition layer, the system analyzes the logic relationship between the first search condition layer AND the next search condition layer, such as NAND AND NOT, whether the same level variable exists, if so, the query statement is recombined in the current layer, AND the like, the logic relationship analysis is performed on the current search condition layer AND the search condition layer of the previous layer, AND if the same level variable exists between the current search condition layer AND the search condition layer of the previous layer, the same level variable is combined to obtain each search condition layer. Each retrieval condition layer sequentially presents a funnel type structure.
And each lower search condition layer starts from the second search condition layer, performs analysis, generates a query sentence and a search action within the range of the sample size of the previous search condition layer, and obtains the sample size of each search condition layer meeting the search condition, the search results such as the association key and the like. Each search condition layer is contained on the previous search condition layer, so that when searching, after the current search condition layer generates a query statement, the sample data set of the current search condition layer is screened out by using the query statement in the sample data set obtained by searching the previous search condition layer.
And finally, gradually refining the search conditions by the current insight group, wherein the last search condition layer obtained by the current insight group is the nano-row condition of the current insight group, and the search result corresponding to the nano-row condition is the search result of the current insight group. Each layer of search condition layer is configured in a layered manner in a funnel type search mode, each layer of search condition layer carries out nano-ranking on medical data, each layer of search condition layer supports a complete variable search function, and each layer of search condition layer can be independently searched to obtain a search result. The layers are supported to be combined in a ' and ' non ' mode to support continuous refinement of the data range to obtain a last layer of retrieval condition layer, wherein the last layer of retrieval condition layer is an optimal condition layer meeting the investigation requirement of researchers, namely, the final nano-array condition is obtained, the retrieval result of the last layer of retrieval condition layer is medical data meeting the requirement of the researchers, namely, the sample size and the association key obtained by retrieving the last layer of retrieval condition layer are the final retrieval result.
In an embodiment, the comparison and analysis module 130 is connected to the search module 120, and is configured to compare and analyze the search result of each insight group to obtain an optimal insight group and a corresponding nanobar condition according to the user's insight requirement.
It should be explained that, in the process of retrieving medical data, there are usually multiple insight groups, the comparison analysis function can be started on the page for the retrieval results of the multiple insight groups, the comparison analysis module 130 of the system can calculate and generate the quality details of the compared variables and the overview of the sample data according to the sample data obtained by the last retrieval condition layer (nano-arranging condition) of each insight group and the variables uniformly selected by the user, such as the filling rates of the white blood cell count filling rate under the two insight groups respectively, and the optimal insight group and the nano-arranging condition corresponding to the optimal insight group meeting the requirement of the user insight are selected according to the comparison result.
The sample data obtained by the last retrieval condition layer (nano-array condition) of each insight group is sample PVE data, and the sample PVE data specifically comprises:
P (patient) the representation field is patient dimension, such as patient basic information, and only one piece of data is identified for one patient, so that the data cannot be repeated and cannot be increased with the increase of the number of times of visits.
V (visit), which is the dimension of the visit, such as the basic information of the visit, only one piece of data is identified for one patient visit, and the data is not repeated and does not increase with the increase of the examination times of single visit.
E (event), which means that the domain is an event dimension, and all but P and V belong to the event dimension, such as diagnosis information, examination information, etc., and event dimension data occurs multiple times in one visit.
The variable/index is an index within the PVE data field, such as in the P patient basic information field, and the patient name is a variable or index in the dataset.
PVEs are related to each other, namely one P is to many V, one V is to many E, and many E is to many E (such as surgical treatment and surgical details).
In one embodiment, the system further comprises a result display module, wherein the result display module is used for visually displaying the search result according to the observation index set by the user.
In order to help researchers check the data quality and direction in the research process, the system supports to flexibly check the patient overview information of each search condition layer, the concerned variable filling rate information, the value range distribution of the variables, the data quality and other search result information, and the researchers can conveniently confirm and continuously optimize the exploration conditions and direction through the visualized report and the data overview information.
Specifically, the user can flexibly select and set the observation index on the system foreground page so as to retrieve and display the corresponding retrieval result. For example, the user may select a specific search condition layer, or default to display the last search condition layer, the researcher further selects an observation variable or an observation index, the system may automatically display the matched sample data, and the matched sample data may be displayed in a sample data form and a chart overview form, where the display types may include, but are not limited to, the value range distribution condition of the sample variable, the data filling rate of the variable, the final result, the variable overview, and the like.
In an embodiment, the result display module may be further configured to visually display results of the comparative analysis of the plurality of insight groups.
The system can also display the comparison analysis results of each insight group at the result display module, and calculate and generate the quality detail of the compared variables, the overview of the sample data and the like, for example, the filling rate of the blood white cell count under the two insight groups respectively according to the sample data obtained by the last retrieval condition layer of each insight group and the observation variables or the observation indexes uniformly selected by researchers. Sample data in the retrieval process can be displayed in an intuitive visual form through the result display module, so that a user can conveniently analyze and select an optimal insight group and a corresponding nano-array condition, and scientific researchers can conveniently, rapidly and accurately explore medical data and research directions.
The invention can progressively explore and verify the research direction by the funnel type searching method, and does not need to combine various searching conditions and repeatedly modify the searching conditions at one time, thereby obviously reducing the repeated workload in the exploration process, saving the cost and improving the research efficiency. In addition, the system also provides an intra-hospital code comparison function, so that a user can clearly see the corresponding relation between an intra-hospital original noun and a normalized standard medical term, for example, the standard noun corresponding to 'congenital heart disease'. The invention supports flexible retrieval of term variables and term value fields, a user can search specific diagnosis standard nouns such as 'congenital heart disease', and can also search specific test indexes such as 'blood white cell count is greater than 5', at this time 'congenital heart disease' can be used as the value field of search, and 'blood white cell count' can be used as one variable of the test indexes for retrieval. The invention supports the multi-element comparison function of result display and sample data, and a user can comprehensively and accurately acquire the difference of variables among different samples by selecting a plurality of insight groups and performing comparison analysis, so that powerful data support is provided for subsequent research by researchers.
It is emphasized that the funnel type medical data insight system supports layering to carry out nano-ranking on medical data, each layer of search condition layer supports complete variable search function, each layer of search condition layer continuously refines a data range to obtain final nano-ranking conditions, in order to help researchers check data quality and research directions in a research process, support to flexibly check search result information such as patient overview information, concerned variable filling rate information, value domain distribution of variables, data quality and the like of each search condition layer, and the researchers can conveniently confirm and continuously optimize search conditions and directions through visual report forms and data overview information, and further support to carry out comparison analysis on multiple insight groups to obtain nano-ranking conditions with better effects, thereby providing assistance for the researchers to carry out subsequent research.
To facilitate the presentation of the funnel medical data insight system and the funnel medical data insight method of the present application, the following specific examples are provided in connection with fig. 2 to 7:
for example, the study of differences between the sample size, the number of people, and the final effect of different treatment regimens in the home for diseases diagnosed as ventricular septal defects involves variables including diagnosis name, diagnosis time, medication name, drug dosage, drug type, surgical name, etc.
And 1, configuring a plurality of insight groups according to the insight requirements of researchers. As shown in fig. 3, the disease of ventricular septal defect is divided into two insight groups on the system page, ventricular septal defect drug therapy and ventricular septal defect drug therapy surgery.
And 2, configuring each layer of retrieval condition layer in a layered manner. As shown in fig. 4, each insight group selects a search variable to configure a search condition, and adopts a funnel type search method to gradually refine and configure each layer of search condition layers.
And 3, correspondingly generating query sentences according to the retrieval condition layers of each layer by the system. And generating a query statement in the system according to the retrieval conditions of the retrieval condition layer.
And 4, carrying out hierarchical query and storing the sample size and the associated key of each layer. And performing search within the whole data set based on the query statement to obtain the sample size meeting the search condition and the associated key.
And 5, extracting sample data according to the association key and the observation index, and checking data conditions such as data overview, variable filling rate, value range distribution, comparison results and the like. As shown in fig. 5, the researcher selects the observation index to visually display the search result, and views the overview, report, and the like.
And 6, comparing and analyzing a plurality of groups of insight groups to obtain the nano-array condition meeting the insight requirement. After the comparative analysis is performed, as shown in fig. 6 and fig. 7, a researcher can also select an observation index in the system, visually display the comparative analysis results of multiple insight groups, and intuitively display and select an optimal insight group.
In the embodiment of the application, the words "first", "second", etc. are used to distinguish identical items or similar items having substantially the same function and action, and the sequence thereof is not limited. It will be appreciated by those of skill in the art that the words "first," "second," and the like do not limit the amount and order of execution, and that the words "first," "second," and the like do not necessarily differ.
In the embodiments of the present application, words such as "exemplary" or "such as" denote examples, illustrations, or descriptions. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.
In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "and/or" describes an association of associated objects, meaning that there may be three relationships, e.g., A and/or B, and that there may be A alone, while A and B are present, and B alone, where A, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (a, b or c) of a, b, c, a-b, a-c, b-c or a-b-c may be represented, wherein a, b, c may be single or plural.
Fig. 8 is a schematic block diagram of a funnel-type medical data insight method provided by an embodiment of the present application, the funnel-type medical data insight method being applied to the funnel-type medical data insight system as described above. As shown in fig. 8, the funnel-type medical data insight method includes:
step S81, configuring one or more insight groups according to user insight requirements;
Step S82, medical data is searched by adopting a funnel type search method based on each insight group so as to obtain a nano-array condition and a search result corresponding to each insight group;
and step S83, comparing and analyzing the search result of each insight group to obtain an optimal insight group meeting the user insight requirement and a corresponding nano-array condition.
It should be understood that the specific processes of the above corresponding steps are already described in the above embodiments, and are not repeated here for brevity.
It should also be understood that the division of the modules in the embodiment of the present application is merely a logic function division, and other division manners may be actually implemented. In addition, each functional module in the embodiments of the present application may be integrated in one processor, or may exist alone physically, or two or more modules may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules.
Fig. 9 is a schematic block diagram of an electronic terminal provided in an embodiment of the present application. As shown in fig. 9, the electronic terminal comprises at least one processor 901, a memory 902, at least one network interface 903, and a user interface 905. The various components in the device are coupled together by a bus system 904. It is to be appreciated that the bus system 904 is employed to facilitate connected communications between these components. The bus system 904 includes a power bus, a control bus, and a status signal bus in addition to a data bus. But for clarity of illustration the various buses are labeled as bus systems in fig. 9.
The user interface 905 may include, among other things, a display, keyboard, mouse, trackball, click gun, keys, buttons, touch pad, or touch screen, etc.
It is to be appreciated that the memory 902 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read Only Memory (ROM), a programmable Read Only Memory (PROM, programmable Read-Only Memory), which serves as an external cache, among others. By way of example, and not limitation, many forms of RAM are available, such as static random Access Memory (SRAM, staticRandom Access Memory), synchronous static random Access Memory (SSRAM, synchronous Static RandomAccess Memory). The memory described by embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.
The memory 902 in the embodiment of the present invention is used to store various kinds of data to support the operation of the electronic terminal 900. Examples of such data include any executable programs for operating on the electronic terminal 900, such as an operating system 9021 and application programs 9022, and the operating system 9021 contains various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application 9022 may include various applications such as a media player (MEDIA PLAYER), browser (Browser), etc. for implementing various application services. The method for implementing the funnel-type medical data insight provided by the embodiment of the invention can be contained in the application program 9022.
The method disclosed in the above embodiment of the present invention may be applied to the processor 901 or implemented by the processor 901. Processor 901 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in the processor 901 or instructions in the form of software. The Processor 901 may be a general purpose Processor, a digital signal Processor (DSP, digital Signal Processor), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Processor 901 may implement or perform the methods, steps and logic blocks disclosed in embodiments of the present invention. The general purpose processor 901 may be a microprocessor or any conventional processor or the like. The steps of the accessory optimization method provided by the embodiment of the invention can be directly embodied as the execution completion of the hardware decoding processor or the execution completion of the hardware and software module combination execution in the decoding processor. The software modules may be located in a storage medium having memory and a processor reading information from the memory and performing the steps of the method in combination with hardware.
In an exemplary embodiment, the electronic terminal 900 may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, programmable logic devices (PLDs, programmable Logic Device), complex programmable logic devices (CPLDs, complex Programmable Logic Device) for performing the aforementioned methods.
According to a method provided by an embodiment of the present application, there is also provided a computer program product comprising computer program code which, when run on a computer, causes the computer to perform the method of funnel medical data insight of any of the illustrated embodiments.
According to a method provided by an embodiment of the present application, the present application further provides a computer-readable storage medium storing program code that, when run on a computer, causes the computer to perform the method of funnel medical data insight of any of the illustrated embodiments.
As used in this specification, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a computing device and the computing device can be a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between 2 or more computers. Furthermore, these components can execute from various computer readable media having various data structures stored thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from two components interacting with one another in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).
Those of ordinary skill in the art will appreciate that the various illustrative logical blocks (illustrative logical block) and steps (steps) described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components 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 units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
In the above-described embodiments, the functions of the respective functional units may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions (programs). When the computer program instructions (program) are loaded and executed on a computer, the processes or functions in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by a wired (e.g., coaxial cable, fiber optic, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). Computer readable storage media can be any available media that can be accessed by a computer or data storage devices, such as servers, data centers, etc., that contain an integration of one or more available media. Usable media may be magnetic media (e.g., floppy disks, hard disks, magnetic tape), optical media (e.g., high density digital video discs (digital video disc, DVD), or semiconductor media (e.g., solid State Drives (SSDs)), etc.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present application. The storage medium includes a U disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
In summary, the application provides a funnel type medical data insight system, a method, a medium, a program product and a terminal, which comprise a configuration module, a search module and a comparison analysis module, wherein the configuration module is used for configuring one or more insight groups according to user insight requirements, the search module is connected with the configuration module and is used for searching medical data by adopting a funnel type search method based on each insight group to obtain nanorow conditions and search results corresponding to each insight group, and the comparison analysis module is connected with the search module and is used for comparing and analyzing the search results of each insight group to obtain an optimal insight group and the nanorow conditions corresponding to the optimal insight group meeting the user insight requirements. The application supports layering medical data to carry out nano-ranking, each layer of search condition layer supports complete variable search function, each layer of search condition layer continuously refines the data range to obtain the final nano-ranking condition, in order to help researchers check the data quality and research direction in the research process, supports to flexibly check the patient overview information, the concerned variable filling rate information, the value range distribution of the variable, the data quality and other search result information of each search condition layer, and can conveniently confirm and continuously optimize the exploration condition and direction through the visualized report and the data overview information. Therefore, the application effectively overcomes various defects in the prior art and has high industrial utilization value.
The above embodiments are merely illustrative of the principles of the present application and its effectiveness, and are not intended to limit the application. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the application. Accordingly, it is intended that all equivalent modifications and variations of the application be covered by the claims, which are within the ordinary skill of the art, be within the spirit and scope of the present disclosure.
Claims (9)
1. A funnel-type medical data insight system, comprising:
The system comprises a configuration module, a corresponding insight group, a disease research requirement aiming at any disease research requirement of scientific researchers, a disease treatment module and a disease treatment module, wherein the configuration module is used for configuring a plurality of insight groups according to the user insight requirement, wherein the user insight requirement is the research requirement of a user on medical data;
The retrieval module is connected with the configuration module and is used for retrieving the medical data by adopting a funnel type retrieval method based on each insight group so as to obtain the nano-arrangement condition and the retrieval result corresponding to each insight group; for any insight group, adopting a funnel type searching method to gradually refine searching conditions so as to obtain a plurality of searching condition layers of the insight group, wherein a sequential containing relation exists among the searching condition layers;
The process for searching the medical data by adopting the funnel type search method comprises the steps of configuring search conditions on a foreground page by a user in a layered manner, searching the medical data based on the search conditions of the current search condition layer to obtain corresponding search results, evaluating the search results of the current search condition layer by the user, and further refining and setting the search conditions by the user to obtain the next search condition layer if the search results of the current search condition layer do not accord with expectations;
starting from the second retrieval condition layer, each layer of retrieval condition layer below the second retrieval condition layer performs analysis and generates query sentences and retrieval actions within the range of the sample size of the last retrieval condition layer to obtain a retrieval result of each layer of retrieval condition layer conforming to the retrieval condition;
The comparison analysis module is connected with the search module and is used for comparing and analyzing the search result of each insight group to obtain an optimal insight group meeting the user insight requirement and a corresponding nano-array condition, wherein the observation variable is uniformly selected by a user according to the search result of each insight group, the quality detail of the variable after comparison and the overview of sample data are calculated and generated, and the optimal insight group meeting the user insight requirement and the corresponding nano-array condition are selected by the user according to the comparison result.
2. The funnel medical data insight system of claim 1, wherein a query statement is generated based on a search condition of a current search condition layer, to query and search medical data based on the query statement.
3. The funnel medical data insight system of claim 2, wherein the plurality of search criteria layers of each insight group each search medical data based upon search criteria of a current search criteria layer to obtain a corresponding search result.
4. The system of claim 1, further comprising a result display module for visually displaying the search result according to an observation index set by a user.
5. The system of claim 4, wherein the results display module is further configured to visually display results of the comparative analysis of the plurality of insight groups.
6. A method of funnel medical data insight as applied to the funnel medical data insight system of any of the claims 1 to 5, the method comprising:
The method comprises the steps of configuring a plurality of insight groups according to user insight requirements, configuring corresponding insight groups based on the user research requirements on medical data, configuring corresponding insight groups based on different treatment schemes of diseases according to any disease research requirements of scientific researchers, and acquiring a plurality of information groups based on the user research requirements on the medical data;
Based on each insight group, searching the medical data by adopting a funnel type searching method so as to obtain a nano-array condition and a searching result corresponding to each insight group; for any insight group, adopting a funnel type searching method to gradually refine searching conditions so as to obtain a plurality of searching condition layers of the insight group, wherein a sequential containing relation exists among the searching condition layers;
The process for searching the medical data by adopting the funnel type search method comprises the steps of configuring search conditions on a foreground page by a user in a layered manner, searching the medical data based on the search conditions of the current search condition layer to obtain corresponding search results, evaluating the search results of the current search condition layer by the user, and further refining and setting the search conditions by the user to obtain the next search condition layer if the search results of the current search condition layer do not accord with expectations;
starting from the second retrieval condition layer, each layer of retrieval condition layer below the second retrieval condition layer performs analysis and generates query sentences and retrieval actions within the range of the sample size of the last retrieval condition layer to obtain a retrieval result of each layer of retrieval condition layer conforming to the retrieval condition;
And comparing and analyzing the search results of each insight group to obtain an optimal insight group and a corresponding nano-ranking condition according to the user insight requirement, wherein the search results of each insight group are combined with the observation variables uniformly selected by the user to calculate and generate an overview of quality details of the compared variables and sample data, and the optimal insight group and the corresponding nano-ranking condition according to the comparison result are used for helping the user to select the optimal insight group and the corresponding nano-ranking condition according to the user insight requirement.
7. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the funnel-type medical data insight method of claim 6.
8. A computer program product, characterized in that the computer program product comprises computer program code which, when run on a computer, causes the computer to implement the funnel medical data insight method of claim 6.
9. An electronic terminal comprising a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement the funnel medical data insight method of claim 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411276465.XA CN118782266B (en) | 2024-09-12 | 2024-09-12 | Funnel-type medical data insight system, method, medium, program product and terminal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411276465.XA CN118782266B (en) | 2024-09-12 | 2024-09-12 | Funnel-type medical data insight system, method, medium, program product and terminal |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118782266A CN118782266A (en) | 2024-10-15 |
| CN118782266B true CN118782266B (en) | 2025-02-14 |
Family
ID=92979381
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202411276465.XA Active CN118782266B (en) | 2024-09-12 | 2024-09-12 | Funnel-type medical data insight system, method, medium, program product and terminal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118782266B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110781281A (en) * | 2019-10-24 | 2020-02-11 | 北京工业大学 | Detection methods, devices, computer equipment and storage media for emerging topics |
| CN114385825A (en) * | 2021-12-14 | 2022-04-22 | 上海工程技术大学 | Auxiliary formulating system and method for nano-grade standard |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019070925A1 (en) * | 2017-10-06 | 2019-04-11 | Elsevier, Inc. | Systems and methods for providing recommendations for academic and research entities |
| CN107657991B (en) * | 2017-11-13 | 2021-01-29 | 医渡云（北京）技术有限公司 | Patient data screening method and device, storage medium and electronic equipment |
| CN116150475B (en) * | 2022-11-30 | 2024-01-02 | 北京百度网讯科技有限公司 | Information retrieval method, device, electronic equipment and storage medium |
| CN116313125A (en) * | 2023-02-15 | 2023-06-23 | 北京百度网讯科技有限公司 | Data processing method, device, equipment and storage medium |
| CN117407577A (en) * | 2023-09-27 | 2024-01-16 | 同方知网数字出版技术股份有限公司 | Document analysis assistant system, method, electronic equipment and media |
| CN118227889A (en) * | 2024-04-22 | 2024-06-21 | 重庆医科大学 | A biomedical statistics consulting service system and method |
-
2024
- 2024-09-12 CN CN202411276465.XA patent/CN118782266B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110781281A (en) * | 2019-10-24 | 2020-02-11 | 北京工业大学 | Detection methods, devices, computer equipment and storage media for emerging topics |
| CN114385825A (en) * | 2021-12-14 | 2022-04-22 | 上海工程技术大学 | Auxiliary formulating system and method for nano-grade standard |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118782266A (en) | 2024-10-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9171104B2 (en) | Iterative refinement of cohorts using visual exploration and data analytics | |
| Gotz et al. | A methodology for interactive mining and visual analysis of clinical event patterns using electronic health record data | |
| US8756077B2 (en) | Personalized health records with associative relationships | |
| US20220115100A1 (en) | Systems and methods for retrieving clinical information based on clinical patient data | |
| US11288279B2 (en) | Cognitive computer assisted attribute acquisition through iterative disclosure | |
| US20140130178A1 (en) | Automated Determination of Quasi-Identifiers Using Program Analysis | |
| US20120207362A1 (en) | Mapping of literature onto regions of interest on neurological images | |
| JP6187474B2 (en) | Medical information analysis program, medical information analysis apparatus, and medical information analysis method | |
| US20140257847A1 (en) | Hierarchical exploration of longitudinal medical events | |
| US20190287660A1 (en) | Generating and applying subject event timelines | |
| WO2017158472A1 (en) | Relevance feedback to improve the performance of clustering model that clusters patients with similar profiles together | |
| US20150106022A1 (en) | Interactive visual analysis of clinical episodes | |
| JPWO2015186205A1 (en) | Medical data search system | |
| JP7437386B2 (en) | How to categorize medical records | |
| US20080175460A1 (en) | Pacs portal with automated data mining and software selection | |
| Miotto et al. | eTACTS: a method for dynamically filtering clinical trial search results | |
| EP3074894A1 (en) | A system and method to pre-fetch comparison medical studies | |
| Bannach et al. | Visual analytics for radiomics: Combining medical imaging with patient data for clinical research | |
| Aoki et al. | Searching the literature: four simple steps. | |
| Nair et al. | Preserving narratives in electronic health records | |
| US20190197135A1 (en) | Intelligently Organizing Displays of Medical Imaging Content for Rapid Browsing and Report Creation | |
| Hsu et al. | MEDPLAN: A Two-Stage RAG-Based System for Personalized Medical Plan Generation | |
| Cerquitelli et al. | Data mining for better healthcare: A path towards automated data analysis? | |
| CN118782266B (en) | Funnel-type medical data insight system, method, medium, program product and terminal | |
| CN106663144A (en) | Method and apparatus for hierarchical data analysis based on cross-correlation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |