Journal article

Machine learning-XGBoost analysis of language networks to classify patients with epilepsy.

L Torlay, M Perrone-Bertolotti, E Thomas, M Baciu

Brain Informatics | Published : 2017

Abstract

Our goal was to apply a statistical approach to allow the identification of atypical language patterns and to differentiate patients with epilepsy from healthy subjects, based on their cerebral activity, as assessed by functional MRI (fMRI). Patients with focal epilepsy show reorganization or plasticity of brain networks involved in cognitive functions, inducing 'atypical' (compared to 'typical' in healthy people) brain profiles. Moreover, some of these patients suffer from drug-resistant epilepsy, and they undergo surgery to stop seizures. The neurosurgeon should only remove the zone generating seizures and must preserve cognitive functions to avoid deficits. To preserve functions, one shou..

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Grants

Awarded by ANR Grant Infrastructure d'Avenir en Biologie Santé