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

Theme Issue: ChatGPT and Generative Language Models in Medical Education (66) Artificial Intelligence (1186) Viewpoint and Opinions on Innovation in Medical Education (52) Health Informatics Education and Training (43)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46344, first published .
Data Science as a Core Competency in Undergraduate Medical Education in the Age of Artificial Intelligence in Health Care

Data Science as a Core Competency in Undergraduate Medical Education in the Age of Artificial Intelligence in Health Care

Data Science as a Core Competency in Undergraduate Medical Education in the Age of Artificial Intelligence in Health Care

Authors of this article:

Puneet Seth1 Author Orcid Image ;   Nancy Hueppchen2 Author Orcid Image ;   Steven D Miller3 Author Orcid Image ;   Frank Rudzicz4, 5, 6 Author Orcid Image ;   Jerry Ding7 Author Orcid Image ;   Kapil Parakh8 Author Orcid Image ;   Janet D Record2 Author Orcid Image
Article Authors Cited by (5) Tweetations (24) Metrics

Journals

  1. Jowsey T, Stokes-Parish J, Singleton R, Todorovic M. Medical education empowered by generative artificial intelligence large language models. Trends in Molecular Medicine 2023;29(12):971 View
  2. Khlaif Z, Mousa A, Hattab M, Itmazi J, Hassan A, Sanmugam M, Ayyoub A. The Potential and Concerns of Using AI in Scientific Research: ChatGPT Performance Evaluation. JMIR Medical Education 2023;9:e47049 View
  3. Jacobs S, Lundy N, Issenberg S, Chandran L. Reimagining Core Entrustable Professional Activities for Undergraduate Medical Education in the Era of Artificial Intelligence. JMIR Medical Education 2023;9:e50903 View
  4. Meyer A, Riese J, Streichert T. Comparison of the Performance of GPT-3.5 and GPT-4 With That of Medical Students on the Written German Medical Licensing Examination: Observational Study. JMIR Medical Education 2024;10:e50965 View