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

Formative Evaluation of Digital Health Interventions (3524) Clinical Information and Decision Making (2113) Machine Learning (2270) JMIR Theme Issue: COVID-19 Special Issue (2569)

Published on in Vol 10 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/76542, first published .
Evaluating Biomedical Feature Fusion on Machine Learning’s Predictability and Interpretability of COVID-19 Severity Types: Model Development, Interpretation, and Validation

Evaluating Biomedical Feature Fusion on Machine Learning’s Predictability and Interpretability of COVID-19 Severity Types: Model Development, Interpretation, and Validation

Evaluating Biomedical Feature Fusion on Machine Learning’s Predictability and Interpretability of COVID-19 Severity Types: Model Development, Interpretation, and Validation

Authors of this article:

Haleigh Noelle West-Page1 Author Orcid Image ;   Kevin McGoff1 Author Orcid Image ;   Harrison Latimer1 Author Orcid Image ;   Isaac Olufadewa2 Author Orcid Image ;   Shi Chen2 Author Orcid Image
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