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

Viewpoint and Opinions on Technology and Innovation in Public Health (69) Machine Learning (2229) AI Applications in Public Health (37) Artificial Intelligence (2347) Data Science (390) Knowledge Translation and Implementation Science (576) Big Data for Health Promotion and Health Equity (56) Ethical, Legal, and Social Implications of Public Health Informatics (20)

Published on in Vol 11 (2025)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68952, first published .
Machine Learning Applications in Population and Public Health: Guidelines for Development, Testing, and Implementation

Machine Learning Applications in Population and Public Health: Guidelines for Development, Testing, and Implementation

Machine Learning Applications in Population and Public Health: Guidelines for Development, Testing, and Implementation

Authors of this article:

Andrew D Pinto1, 2, 3, 4 Author Orcid Image ;   Sharon Birdi1 Author Orcid Image ;   Steve Durant1 Author Orcid Image ;   Roxana Rabet1 Author Orcid Image ;   Rahul Parekh1, 5 Author Orcid Image ;   Shehzad Ali6, 7, 8 Author Orcid Image ;   David Buckeridge9 Author Orcid Image ;   Marzyeh Ghassemi10 Author Orcid Image ;   Jennifer Gibson11 Author Orcid Image ;   Ava John-Baptiste12 Author Orcid Image ;   Jillian Macklin1, 13 Author Orcid Image ;   Melissa D McCradden4, 14, 15 Author Orcid Image ;   Kwame McKenzie16, 17 Author Orcid Image ;   Parisa Naraei18 Author Orcid Image ;   Akwasi Owusu-Bempah19 Author Orcid Image ;   Laura C Rosella4, 20, 21, 22 Author Orcid Image ;   James Shaw23 Author Orcid Image ;   Ross Upshur3, 4, 11 Author Orcid Image ;   Sharmistha Mishra24, 25, 26, 27, 28 Author Orcid Image
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