Klepachevskyi et al., 2024 - Google Patents
Magnetoencephalography-based interpretable automated differential diagnosis in neurodegenerative diseasesKlepachevskyi et al., 2024
View PDF- Document ID
- 11960076893473210531
- Author
- Klepachevskyi D
- Romano A
- Aristimunha B
- Angiolelli M
- Trojsi F
- Bonavita S
- Sorrentino G
- Andreone V
- Minino R
- Lopez E T
- Polverino A
- Jirsa V
- Saudargienė A
- Corsi M
- Sorrentino P
- Publication year
- Publication venue
- medRxiv
External Links
Snippet
Automating the diagnostic process steps has been of interest for research grounds and to help manage the healthcare systems. Improved classification accuracies, provided by ever more sophisticated algorithms, were mirrored by the loss of interpretability on the criteria for …
- 238000002582 magnetoencephalography 0 title abstract description 19
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
- G06F19/322—Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/22—Health care, e.g. hospitals; Social work
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
- A61B5/0402—Electrocardiography, i.e. ECG
- A61B5/0452—Detecting specific parameters of the electrocardiograph cycle
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/0033—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room
- A61B5/004—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room adapted for image acquisition of a particular organ or body part
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4076—Diagnosing or monitoring particular conditions of the nervous system
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Khozeimeh et al. | RF-CNN-F: random forest with convolutional neural network features for coronary artery disease diagnosis based on cardiac magnetic resonance | |
| Candia-Rivera et al. | Neural responses to heartbeats detect residual signs of consciousness during resting state in postcomatose patients | |
| Zhao et al. | Diagnosis of autism spectrum disorders using multi-level high-order functional networks derived from resting-state functional mri | |
| Li et al. | Detecting Alzheimer's disease on small dataset: a knowledge transfer perspective | |
| Kriegeskorte et al. | Everything you never wanted to know about circular analysis, but were afraid to ask | |
| Yan et al. | Early-stage identification and pathological development of Alzheimer’s disease using multimodal MRI | |
| Mousavian et al. | Depression detection from sMRI and rs-fMRI images using machine learning | |
| Andreev et al. | Toward interpretability of machine learning methods for the classification of patients with major depressive disorder based on functional network measures | |
| Brammer | The role of neuroimaging in diagnosis and personalized medicine-current position and likely future directions | |
| Wismüller et al. | Classification of schizophrenia from functional MRI using large-scale extended Granger causality | |
| Eslami et al. | Explainable and scalable machine learning algorithms for detection of autism spectrum disorder using fMRI data | |
| Jui et al. | Application of entropy for automated detection of neurological disorders with electroencephalogram signals: a review of the last decade (2012–2022) | |
| Bi et al. | The white matter structural network underlying human tool use and tool understanding | |
| Sorrentino et al. | Whole-brain propagation delays in multiple sclerosis, a combined tractography-magnetoencephalography study | |
| Li et al. | Sparse multivariate autoregressive modeling for mild cognitive impairment classification | |
| Cui et al. | Deep symmetric three-dimensional convolutional neural networks for identifying acute ischemic stroke via diffusion-weighted images | |
| Powell et al. | Local connectome phenotypes predict social, health, and cognitive factors | |
| Liu et al. | Multiscale functional connectome abnormality predicts cognitive outcomes in subcortical ischemic vascular disease | |
| Li et al. | Diagnosis of Alzheimer's disease by feature weighted-LSTM: a preliminary study of temporal features in brain resting-state fMRI | |
| Belmokhtar et al. | Classification of Alzheimer’s disease from 3D structural MRI data | |
| Udayakumar et al. | Connectome-based schizophrenia prediction using structural connectivity-Deep Graph Neural Network (sc-DGNN) | |
| Hu et al. | The influence of white matter hyperintensities severity on functional brain activity in cerebral small vessel disease: An rs-fMRI study | |
| Dai et al. | Climb: Data foundations for large scale multimodal clinical foundation models | |
| Anderson et al. | Classification of spatially unaligned fMRI scans | |
| Siddiqui et al. | Artificial intelligence-based myocardial infarction diagnosis: a comprehensive review of modern techniques |