Automatic Detection and Classification of Epileptic Seizures from EEG Data: Finding Optimal Acquisition Settings and Testing Interpretable Machine Learning Approach

Automatic Detection and Classification of Epileptic Seizures from EEG Data: Finding Optimal Acquisition Settings and Testing Interpretable Machine Learning Approach

Deep learning (DL) is emerging as a successful technique for automatic detection and differentiation of spontaneous seizures that may otherwise be missed or misclassified. Herein, we propose a system architecture based on top-performing DL models for binary and multigroup classifications with the no...

Full description

Bibliographic Details
Main Authors: Yauhen Statsenko, Vladimir Babushkin, Tatsiana Talako, Tetiana Kurbatova, Darya Smetanina, Gillian Lylian Simiyu, Tetiana Habuza, Fatima Ismail, Taleb M. Almansoori, Klaus N.-V. Gorkom, Miklós Szólics, Ali Hassan, Milos Ljubisavljevic
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Biomedicines
Subjects:
deep learning
interpretable machine learning
activation maximization
epileptic seizure
EEG
acquisition settings
Online Access:https://www.mdpi.com/2227-9059/11/9/2370

Internet

https://www.mdpi.com/2227-9059/11/9/2370

Similar Items