Network phenotypes and their clinical significance in temporal lobe epilepsy using machine learning...
Network phenotypes and their clinical significance in temporal lobe epilepsy using machine learning applications to morphological and functional graph theory metrics
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Publisher
London: Nature Publishing Group UK
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Language
English
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Publisher
London: Nature Publishing Group UK
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Contents
Machine learning analyses were performed on graph theory (GT) metrics extracted from brain functional and morphological data from temporal lobe epilepsy (TLE) patients in order to identify intrinsic network phenotypes and characterize their clinical significance. Participants were 97 TLE and 36 healthy controls from the Epilepsy Connectome Project....
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Full title
Network phenotypes and their clinical significance in temporal lobe epilepsy using machine learning applications to morphological and functional graph theory metrics
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TN_cdi_doaj_primary_oai_doaj_org_article_2e4f0fd0a1d946ada8449880184a921e
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2e4f0fd0a1d946ada8449880184a921e
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-022-18495-z
