Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings
Objectives: 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 process in LMICs by...
Egile Nagusiak: | , , , , , , , , , , , , |
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Formatua: | Journal article |
Hizkuntza: | English |
Argitaratua: |
Public Library of Science
2025
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