Abstract

Researchers are working to integrate machine learn- ing (ML) and artificial intelligence (AI) tools to im- prove and develop clinical practice. Machine learn- ing is becoming more important in medical image analysis. One of the fundamental goals of health- care is to provide timely preventative measures by early disease diagnosis and prognosis. This is cer- tainly relevant for epilepsy, which is characterized by recurring and unpredictable episodes. If epilep- tic seizures can be detected in advance, patients can avoid the unfavourable repercussions. Seizure prog- nosis remains an unsolved problem despite decades of research. This is likely to continue partly due to a lack of information to resolve this issue .Promis- ing new advancements in the ML-based techniques have the ability to alter the situation in the detec- tion and prediction of ES. We present a complete re- view of cutting-edge ML techniques for early seizure prediction with the help of EEG signals. We will highlight research gaps and problems and give rec- ommendations for future initiatives.

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