Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Sep 3, 2024
Date Accepted: May 23, 2025
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
A primer and practical recommendations for AI and machine learning terminology in medicine and behavioral sciences
ABSTRACT
Recent applications of artificial intelligence (AI) and machine learning in medicine and behavioral sciences lead to common confusions about the terms used across the public and research communities. In the current paper, we summarize recent developments in this area and clarify the use of basic terms related to AI and machine learning in medicine and behavioral sciences, neuroscience, and psychology, including artificial intelligence (AI) - machine learning (ML) - deep learning (DL), prediction, testing - validation, overfitting, and regularized linear regression. We will provide practical recommendations for the use of these terms and related methods, and we hope this effort can help researchers in different disciplines communicate effectively with respect to AI analyses and translational medicine.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.