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Consolidated reporting guideline recommendations for prognostic and diagnostic machine learning models: CREMLS
Khaled El Emam;
Tiffany I Leung;
Bradley Malin;
William Klement;
Gunther Eysenbach
ABSTRACT
The number of papers presenting machine learning (ML) models that are being submitted, and published, in the Journal of Medical Internet Research and other JMIR Publications journals has steadily increased. Editors and peer reviewers involved in the review process for such manuscripts often go through multiple review cycles to enhance the quality and completeness of reporting. The use of a reporting guideline, or checklist, can help ensure consistency in the quality of submitted (and published) scientific manuscripts and, for instance, avoid instances of missing information. In this Editorial, JMIR Publications journal editors discuss the general JMIR Publications policy with regards to authors’ application of reporting guidelines, then focus specifically on the reporting of machine learning studies in JMIR Publications journals.
Citation
Please cite as:
El Emam K, Leung TI, Malin B, Klement W, Eysenbach G
Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS)