A Robust Framework for Epileptic Seizure Diagnosis: Utilizing GRU-CNN Architectures in EEG Signal Analysis-Reference-Cited by-同舟云学术

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A Robust Framework for Epileptic Seizure Diagnosis: Utilizing GRU-CNN Architectures in EEG Signal Analysis

Published:2024-02-21 Issue: Volume:1 Page:1-6
ISSN:
Container-title:2024 20th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP)
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Author:

Nikoupour Maryam¹,Keyvanpour Mohammad Reza²,Shojaedini Seyed Vahab³

Affiliation:

1. Alzahra University,Data Mining Laboratory,Department of Computer Engineering, Faculty of Engineering,Tehran,Iran

2. Alzahra University,Faculty of Engineering,Department of Computer Engineering,Tehran,Iran

3. Iranian Research Organization for Science and Technology,Department of Electrical Engineering,Tehran,Iran

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10475172/10475200/10475276.pdf?arnumber=10475276

Reference18 articles.

1. Epileptic multi-seizure type classification using electroencephalogram signals from the Temple University Hospital Seizure Corpus: A review

2. Performance Analysis of Data Fusion Methods Applied to Epileptic Seizure Recognition

3. Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson’s disease and schizophrenia

4. Classification of epileptic seizures from electroencephalogram (EEG) data using bidirectional short-term memory (Bi-LSTM) network architecture

5. A Comprehensive Survey on the Detection, Classification, and Challenges of Neurological Disorders

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