Automatic classification of epilepsy types using ontology-based and genetics-based machine learning

摘要

ObjectivesIn the presurgical analysis for drug-resistant focal epilepsies, the definition of the epileptogenic zone, which is the cortical area where ictal discharges originate, is usually carried out by using clinical, electrophysiological and neuroimaging data analysis. Clinical evaluation is based on the visual detection of symptoms during epileptic seizures. This work aims at developing a fully automatic classifier of epileptic types and their localization using ictal symptoms and machine learning methods.