Use of machine learning for predicting levetiracetam treatment outcome in temporal lobe epilepsy: A pharmaco-EEG study

Abstract

Temporal Lobe Epilepsy (TLE) is a common cause of drug-resistant epilepsy. For these patients, the electroencephalogram (EEG) is a pivotal diagnostic neurophysiological technique. In this study, we aim to determine the predictive power for seizure-freedom of 19-channels EEG, measured both before and after three months the initiation of one of the most used anti-seizure medication (ASM), levetiracetam (LEV), in a population of newly diagnosed TLE people using a machine-learning approach.