Abstract
The rapid development of machine learning (ML) applications in healthcare promises to transform the landscape of healthcare. In order for ML advancements to be effectively utilized in clinical care, it is necessary for the medical workforce to be prepared to handle these changes. As physicians in training are exposed to a wide breadth of clinical tools during medical school, this offers an ideal opportunity to introduce ML concepts. A foundational understanding of ML will not only be practically useful for clinicians, but will also address ethical concerns for clinical decision making. While select medical schools have made effort to integrate ML didactics and practice into their curriculum, we argue that foundational ML principles should be taught broadly to medical students across the country.
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Aziz Nazha, Honoraria: DCI, Consulting or Advisory Role: Karyopharm Therapeutics, Tolero Pharmaceuticals, Speakers’ bureau: Novartis, Incyte, Stock ownership: Amazon.
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Nagy, M., Radakovich, N. & Nazha, A. Why Machine Learning Should Be Taught in Medical Schools. Med.Sci.Educ. 32, 529–532 (2022). https://doi.org/10.1007/s40670-022-01502-3
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DOI: https://doi.org/10.1007/s40670-022-01502-3