Machine learning–XGBoost analysis of language networks to classify patients with epilepsy
Machine learning–XGBoost analysis of language networks to classify patients with epilepsy
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Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
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Berlin/Heidelberg: Springer Berlin Heidelberg
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Contents
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 funct...
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Full title
Machine learning–XGBoost analysis of language networks to classify patients with epilepsy
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TN_cdi_doaj_primary_oai_doaj_org_article_02885abbb74f47169f69b1c89e1b6e63
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_02885abbb74f47169f69b1c89e1b6e63
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ISSN
2198-4018
E-ISSN
2198-4026
DOI
10.1007/s40708-017-0065-7
