What do medical students actually need to know about artificial intelligence?
Name
s41746-020-0294-7.pdf
Description
Published version
Size
517.97 KB
Format
Adobe PDF
Checksum (MD5)
beeaecc529db91b4b4f5cd575e3da3fe
Author(s)
McCoy, Liam G.
Nagaraj, Sujay
Morgado, Felipe
Harish, Vinyas
Das, Sunit
Celi, Leo Anthony G.
Date Issued
June 2020
Journal
npj Digital Medicine
Publisher
Springer Science and Business Media
Citation
McCoy, Liam G. et al. "What do medical students actually need to know about artificial intelligence?." npj Digital Medicine 3, 1 (June 2020): 86 © 2020 Springer Nature
Version
Final published version
Abstract
With emerging innovations in artificial intelligence (AI) poised to substantially impact medical practice, interest in training current and future physicians about the technology is growing. Alongside comes the question of what, precisely, should medical students be taught. While competencies for the clinical usage of AI are broadly similar to those for any other novel technology, there are qualitative differences of critical importance to concerns regarding explainability, health equity, and data security. Drawing on experiences at the University of Toronto Faculty of Medicine and MIT Critical Data's "datathons", the authors advocate for a dual-focused approach: combining robust data science-focused additions to baseline health research curricula and extracurricular programs to cultivate leadership in this space.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1038/s41746-020-0294-7
