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

Saravanakumar et al., 2022 - Google Patents

An effective convolutional neural network-based stacked long short-term memory approach for automated Alzheimer's disease prediction

Saravanakumar et al., 2022

View HTML
Document ID
4758768768522078460
Author
Saravanakumar S
Saravanan T
Publication year
Publication venue
Journal of Intelligent & Fuzzy Systems

External Links

Snippet

In today's world, Alzheimer's Disease (AD) is one of the prevalent neurological diseases where early disease prediction can significantly enhance the compatibility of patient treatment. Nevertheless, accurate diagnosis and optimal feature selection play a vital …
Continue reading at dl.acm.org (HTML) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-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
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G06F19/322Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-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
    • G06F19/3487Medical report generation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6279Classification techniques relating to the number of classes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00006Acquiring or recognising fingerprints or palmprints
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00Digital computers in general; Data processing equipment in general
    • G06F15/18Digital 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

Similar Documents

Publication Publication Date Title
Dissanayake et al. Deep learning for patient-independent epileptic seizure prediction using scalp EEG signals
Tutuko et al. AFibNet: an implementation of atrial fibrillation detection with convolutional neural network
Khan et al. D2PAM: epileptic seizures prediction using adversarial deep dual patch attention mechanism
Saravanakumar et al. An effective convolutional neural network-based stacked long short-term memory approach for automated Alzheimer’s disease prediction
Ibrahim et al. Deep‐learning‐based seizure detection and prediction from electroencephalography signals
Kirubakaran et al. Echo state learned compositional pattern neural networks for the early diagnosis of cancer on the internet of medical things platform
Ibrahim et al. A comprehensive review on advancements in artificial intelligence approaches and future perspectives for early diagnosis of Parkinson's disease
KR et al. A multi-dimensional hybrid CNN-BiLSTM framework for epileptic seizure detection using electroencephalogram signal scrutiny
Mahato et al. Analysis of region of interest (RoI) of brain for detection of depression using EEG signal
Delfan et al. A Hybrid Deep Spatiotemporal Attention‐Based Model for Parkinson's Disease Diagnosis Using Resting State EEG Signals
Jaishankar et al. A novel epilepsy seizure prediction model using deep learning and classification
Dutta et al. Time and frequency domain pre-processing for epileptic seizure classification of epileptic EEG signals
Gupta et al. A design of bat-based optimized deep learning model for EEG signal analysis
EP4093270A1 (en) Method and system for personalized prediction of infection and sepsis
Punarselvam A pragmatic approach of Parkinson disease detection using hybrid case-based reasoning neuro-fuzzy classification system over Mobile edge computing
Chukwunweike et al. Applying AI and machine learning for predictive stress analysis and morbidity assessment in neural systems: A MATLAB-based framework for detecting and addressing neural dysfunction
Dhanalakshmi et al. Speech features-based Parkinson’s disease classification using combined SMOTE-ENN and binary machine learning
Cimr et al. Enhancing EEG signal analysis with geometry invariants for multichannel fusion
Kolli et al. Classification and Diagnosis of Heart Diseases Using Fuzzy Logic Based on IoT
Islam et al. Advanced Parkinson’s disease detection: A comprehensive artificial intelligence approach utilizing clinical assessment and neuroimaging samples
Zeng et al. Advancing cardiac diagnostics: Exceptional accuracy in abnormal ECG signal classification with cascading deep learning and explainability analysis
Shetty et al. Detection of Alzheimer's Disease Progression Using Integrated Deep Learning Approaches.
Saranya et al. Automatic detection of epileptic seizure using machine learning-based IANFIS-LightGBM system
Dey et al. U-Healthcare Monitoring Systems: Volume 1: Design and Applications
Assim et al. Epileptic detection based on deep learning: A review