Understanding and training for the impact of large language models and artificial intelligence in healthcare practice: a narrative review

Author(s)
McCoy, Liam G.; Ci Ng, Faye Y.; Sauer, Christopher M.; Yap Legaspi, Katelyn E.; Jain, Bhav; ... Show more
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Abstract
Reports of Large Language Models (LLMs) passing board examinations have spurred medical enthusiasm for their clinical integration. Through a narrative review, we reflect upon the skill shifts necessary for clinicians to succeed in an LLM-enabled world, achieving benefits while minimizing risks. We suggest how medical education must evolve to prepare clinicians capable of navigating human-AI systems.
Date issued
2024-10-07
URI
https://hdl.handle.net/1721.1/157403
Department
Harvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiology
Journal
BMC Medical Education
Publisher
BioMed Central
Citation
McCoy, L.G., Ci Ng, F.Y., Sauer, C.M. et al. Understanding and training for the impact of large language models and artificial intelligence in healthcare practice: a narrative review. BMC Med Educ 24, 1096 (2024).
Version: Final published version
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