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Data Science as a Core Competency in Undergraduate Medical Education in the Age of Artificial Intelligence in Health Care.
Seth, Puneet; Hueppchen, Nancy; Miller, Steven D; Rudzicz, Frank; Ding, Jerry; Parakh, Kapil; Record, Janet D.
Afiliação
  • Seth P; Department of Family Medicine, McMaster University, Hamilton, ON, Canada.
  • Hueppchen N; Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
  • Miller SD; Division of Pediatric Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
  • Rudzicz F; Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada.
  • Ding J; Vector Institute for Artificial Intelligence, Toronto, ON, Canada.
  • Parakh K; Department of Computer Science, University of Toronto, Toronto, ON, Canada.
  • Record JD; Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
JMIR Med Educ ; 9: e46344, 2023 Jul 11.
Article em En | MEDLINE | ID: mdl-37432728
The increasingly sophisticated and rapidly evolving application of artificial intelligence in medicine is transforming how health care is delivered, highlighting a need for current and future physicians to develop basic competency in the data science that underlies this topic. Medical educators must consider how to incorporate central concepts in data science into their core curricula to train physicians of the future. Similar to how the advent of diagnostic imaging required the physician to understand, interpret, and explain the relevant results to patients, physicians of the future should be able to explain to patients the benefits and limitations of management plans guided by artificial intelligence. We outline major content domains and associated learning outcomes in data science applicable to medical student curricula, suggest ways to incorporate these themes into existing curricula, and note potential implementation barriers and solutions to optimize the integration of this content.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article