Epileptic Seizure Prediction Using Patient-Adaptive Transformer Networks

ArXi:2603.26821v1 Announce Type: cross Epileptic seizure prediction from electroencephalographic (EEG) recordings remains challenging due to strong inter-patient variability and the complex temporal structure of neural signals. This paper presents a patient-adaptive transformer framework for short-horizon seizure forecasting. The proposed approach employs a two-stage