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New bio-inspired approach for deep learning techniques applied to neonatal seizures

Authors :
Khelili, Mohamed Akram
Slatnia, Sihem
Kazar, Okba
Mirjalili, Seyedali
Bourekkache, Samir
Ortiz, Guadalupe
Jiang, Yizhang
Source :
International Journal of Medical Engineering and Informatics; 2024, Vol. 16 Issue: 3 p260-273, 14p
Publication Year :
2024

Abstract

Neonatal seizures are a common emergency in the neonatal intensive care unit and their detection using electroencephalography (EEG) recording is one of the biggest challenges that neurologists face. Even though using artificial intelligence methods such as deep learning for computer vision can help to solve these problems, time consumption, complexity, and overfitting or underfitting of the model still limit the application of deep learning. In order to produce a real-time system that can detect neonatal seizures using EEG and solve the problem of the lack of availability of neurologists, a convolution neural network-based marine predator algorithm system is proposed.

Details

Language :
English
ISSN :
17550653 and 17550661
Volume :
16
Issue :
3
Database :
Supplemental Index
Journal :
International Journal of Medical Engineering and Informatics
Publication Type :
Periodical
Accession number :
ejs66223113
Full Text :
https://doi.org/10.1504/IJMEI.2024.138291