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This paper is in the following e-collection/theme issue:

Early Results from COVID-19 Studies (466) Big Data (451) Advanced Data Analytics in eHealth (391) Secondary Use of Clinical Data for Research and Surveillance (677) Machine Learning (3404) Research Methodology - AI (219) Responsible Health AI (279)

Published on in Vol 10 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/88406, first published .
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A Systematic Evaluation of Cohort Selection Criteria and Their Impact on Machine Learning Model Performance and Demographic Disparities in COVID-19 Outcomes: Cohort Study

A Systematic Evaluation of Cohort Selection Criteria and Their Impact on Machine Learning Model Performance and Demographic Disparities in COVID-19 Outcomes: Cohort Study

Authors of this article:

Atefehsadat Haghighathoseini1 Author Orcid Image ;   Janusz Wojtusiak1 Author Orcid Image ;   Hua Min1 Author Orcid Image ;   Nirup M Menon2 Author Orcid Image
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Journals

  1. Ngana L, Wojtusiak J, Haghighathoseini A, Patel B, Desai D, Villanueva C. External validation and adaptation of the Computational Barthel Index Tool in a large nursing home cohort. PLOS Digital Health 2026;5(10):e0001793 View