0000000000866459

AUTHOR

Marcela Perrone-bertolotti

0000-0001-9981-7042

showing 1 related works from this author

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

2017

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 sho…

0301 basic medicinemedicine.medical_specialtyCognitive Neuroscience[SCCO.COMP]Cognitive science/Computer scienceAudiologyExtreme Gradient Boostinglcsh:Computer applications to medicine. Medical informaticsArticle03 medical and health sciencesEpilepsy0302 clinical medicineText miningMachine learningmedicineLanguagelcsh:Computer softwareEpilepsyCognitive mapReceiver operating characteristicbusiness.industryCognitionNeurophysiologymedicine.diseaseMLComputer Science ApplicationsStatistical classificationlcsh:QA76.75-76.765030104 developmental biologyNeurologyBinary classification[ SCCO.COMP ] Cognitive science/Computer sciencelcsh:R858-859.7Artificial intelligencePsychologybusiness030217 neurology & neurosurgeryAtypicalXGBoost
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