Khadija Slama

Hierarchical temporal-separable convolutional-recurrent attention network for EEG-based epileptic seizure prediction

A hybrid deep learning architecture for patient-independent epileptic seizure identification that integrates a Hierarchical Temporal Separable Convolutional Network, a Dual-Stage Bidirectional Recurrent Neural Network, and a Multi-Head Attention Mechanism is proposed, enabling effective extraction of spatial, temporal, and contextual features from non-stationary EEG signals while addressing inter-patient variability.