Bridging data scarcity and explainability in EEG based Alzheimer’s prediction using cGAN augmented GATv2-LSTM networks
Accurate and early diagnosis of Alzheimer’s Disease (AD) is still a key factor in the treatment of the disease and patient health. The proposed model for the current work is an EEG-based multi-classification model which is tested on two separate datasets with different diagnostic classes (Dataset I: Healthy Control (...