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

Editorial (49) Artificial Intelligence (1371) Machine Learning (1465) Digital Science, Open Science (79) Digital Health Reporting Standards, Quality and Transparency in e-Research (71) Development and Evaluation of Research Methods, Instruments and Tools (481) Knowledge Translation and Implementation Science (398)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52508, first published .
Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS)

Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS)

Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS)

Authors of this article:

Khaled El Emam1, 2 Author Orcid Image ;   Tiffany I Leung3, 4 Author Orcid Image ;   Bradley Malin5 Author Orcid Image ;   William Klement2 Author Orcid Image ;   Gunther Eysenbach3, 6 Author Orcid Image
Article Authors Cited by Tweetations (5) Metrics

Khaled El Emam   1, 2 , BEng, PhD ;   Tiffany I Leung   3, 4 , MD, MPH ;   Bradley Malin   5 , BA, MSc, PhD ;   William Klement   2 , PhD ;   Gunther Eysenbach   3, 6 , MD, MPH

1 School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada

2 Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada

3 JMIR Publications, Inc, Toronto, ON, Canada

4 Department of Internal Medicine (adjunct), Southern Illinois University School of Medicine, Springfield, IL, United States

5 Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, United States

6 School of Health Information Science, University of Victoria, Victoria, BC, Canada

Corresponding Author: