| Autor: |
Khelili, Mohamed Akram, Slatnia, Sihem, Kazar, Okba, Mirjalili, Seyedali, Bourekkache, Samir, Ortiz, Guadalupe, Jiang, Yizhang |
| Zdroj: |
International Journal of Medical Engineering and Informatics; 2024, Vol. 16 Issue: 3 p260-273, 14p |
| Abstrakt: |
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. |
| Databáze: |
Supplemental Index |
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