Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study

Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study

Abstract Background Emerging artificial intelligence (AI) technologies have diverse applications in medicine. As AI tools advance towards clinical implementation, skills in how to use and interpret AI in a healthcare setting could become integral for physicians. This study examines undergraduate med...

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Bibliographic Details
Main Authors: Aidan Pucchio, Raahulan Rathagirishnan, Natasha Caton, Peter J. Gariscsak, Joshua Del Papa, Jacqueline Justino Nabhen, Vicky Vo, Wonjae Lee, Fabio Y. Moraes
Format: Article
Language:English
Published: BMC 2022-11-01
Series:BMC Medical Education
Subjects:
Artificial intelligence
Curriculum
Deep learning
Education, medical
Machine intelligence
Machine learning
Online Access:https://doi.org/10.1186/s12909-022-03896-5

Internet

https://doi.org/10.1186/s12909-022-03896-5

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