Epileptic seizure detection and Prediction using Deep learning

Abstract: Numerous methods, including electroencephalography (EEG) and magnetic resonance imaging (MRI), have been proposed to diagnose epileptic seizures. Deep knowledge (DL) is one of the many subfields of artificial intelligence. Conventional machine learning algorithms involving point birth were used prior to the emergence of DL. As a result, their performance was restricted to what the people creating the features by hand could do. However, in DL, the creation of features and type is completely automated. Similar to how the theory of epileptic seizures has advanced significantly, these methods have appeared in numerous medical fields. This study presents a thorough overview of a factory focused on automated epileptic seizure discovery using neuroimaging modalities and DL methods. Different approaches have been suggested to diagnose epilepsy.

Keywords: LSTM, EEG modalities, MRI modalities.