Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings.

Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings.

<h4>Objectives</h4>Approximately 80% of people with epilepsy live in low- and middle-income countries (LMICs), where limited resources and stigma hinder accurate diagnosis and treatment. Clinical machine learning models have demonstrated substantial promise in supporting the diagnostic p...

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Main Authors: Ioana Duta, Symon M Kariuki, Anthony K Ngugi, Angelina Kakooza Mwesige, Honorati Masanja, Daniel M Mwanga, Seth Owusu-Agyei, Ryan Wagner, J Helen Cross, Josemir W Sander, Charles R Newton, Arjune Sen, Gabriel Davis Jones
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-02-01
Series:PLOS Digital Health
Online Access:https://doi.org/10.1371/journal.pdig.0000491
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