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

Reviews in AI (39) Decision Support for Health Professionals (1677) Ontologies, Classifications, and Coding (354) Diabetes Reviews and Scoping Studies (45) Digital Health Reporting Standards, Quality and Transparency in e-Research (160) Machine Learning (2289) Digital Science, Open Science (93) Diabetes Prevention (135)

Published on in Vol 5 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/87819, first published .
Methodological Approaches to and Reported Performance of Applications of Automated Machine Learning in Diabetes Risk Prediction: Rapid Review

Methodological Approaches to and Reported Performance of Applications of Automated Machine Learning in Diabetes Risk Prediction: Rapid Review

Methodological Approaches to and Reported Performance of Applications of Automated Machine Learning in Diabetes Risk Prediction: Rapid Review

Authors of this article:

Alexandre Castonguay1 Author Orcid Image ;   Sandrine Hegg-Deloye1, 2 Author Orcid Image ;   Arthur Chatton2, 3 Author Orcid Image ;   Amélie Goyette3 Author Orcid Image
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