[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Delfan et al., 2024 - Google Patents

A Hybrid Deep Spatiotemporal Attention‐Based Model for Parkinson's Disease Diagnosis Using Resting State EEG Signals

Delfan et al., 2024

View PDF
Document ID
5445726479742094757
Author
Delfan N
Shahsavari M
Hussain S
Damaševičius R
Acharya U
Publication year
Publication venue
International Journal of Imaging Systems and Technology

External Links

Snippet

ABSTRACT Parkinson's disease (PD), a severe and progressive neurological illness, affects millions of individuals worldwide. For effective treatment and management of PD, an accurate and early diagnosis is crucial. This study presents a deep learning‐based model …
Continue reading at arxiv.org (PDF) (other versions)

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
    • 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
    • G06F19/3487—Medical report generation
    • 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
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • 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
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/04—Inference methods or devices
    • 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
    • G06K9/00006—Acquiring or recognising fingerprints or palmprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
    • 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
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • 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

Similar Documents

Publication Publication Date Title
Pahuja et al. A comparative study of existing machine learning approaches for Parkinson's disease detection
Kumar et al. Brain wave classification using long short-term memory network based OPTICAL predictor
Hassan et al. Fusion of multivariate EEG signals for schizophrenia detection using CNN and machine learning techniques
Ullah et al. Classification of arrhythmia in heartbeat detection using deep learning
Tutuko et al. AFibNet: an implementation of atrial fibrillation detection with convolutional neural network
Li et al. Graph-generative neural network for EEG-based epileptic seizure detection via discovery of dynamic brain functional connectivity
Shaban et al. Resting-state electroencephalography based deep-learning for the detection of Parkinson’s disease
Gliner et al. Automatic classification of healthy and disease conditions from images or digital standard 12-lead electrocardiograms
Dong et al. Subject sensitive EEG discrimination with fast reconstructable CNN driven by reinforcement learning: A case study of ASD evaluation
Moctezuma et al. Towards a minimal EEG channel array for a biometric system using resting-state and a genetic algorithm for channel selection
Delfan et al. A Hybrid Deep Spatiotemporal Attention‐Based Model for Parkinson's Disease Diagnosis Using Resting State EEG Signals
Husnain et al. AI-Driven Integrated Hardware and Software Solution for EEG-Based Detection of Depression and Anxiety
Li et al. Parkinson’s disease detection and classification using EEG based on deep CNN-LSTM model
Siuly et al. SchizoGoogLeNet: The GoogLeNet‐Based Deep Feature Extraction Design for Automatic Detection of Schizophrenia
Agrawal et al. ElectroCardioGram (ECG)-based user authentication using deep learning algorithms
Nawaz et al. Cloud-based healthcare framework for real-time anomaly detection and classification of 1-D ECG signals
US20220391760A1 (en) Combining model outputs into a combined model output
Chawla et al. Computer-aided diagnosis of autism spectrum disorder from EEG signals using deep learning with FAWT and multiscale permutation entropy features
Siuly et al. An efficient Parkinson's disease detection framework: Leveraging time-frequency representation and AlexNet convolutional neural network
Jemal et al. Domain adaptation for EEG-based, cross-subject epileptic seizure prediction
Saravanakumar et al. An effective convolutional neural network-based stacked long short-term memory approach for automated Alzheimer’s disease prediction
Ranjan et al. Multiresolution feature fusion for smart diagnosis of schizophrenia in adolescents using EEG signals
Dhanalakshmi et al. Speech features-based Parkinson’s disease classification using combined SMOTE-ENN and binary machine learning
Zhao et al. Residual and bidirectional LSTM for epileptic seizure detection
Roncero-Parra et al. Inter-hospital moderate and advanced Alzheimer's disease detection through convolutional neural networks