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

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.

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Date Issued:
07.10.2024
URN:
urn:nbn:de:hbz:465-20251212-110833-8
DOI:
10.1186/s12909-024-06048-z
Language:
English
Type of Resource:
Text
Keywords:
  1. Language Model
    Typ
    Schlagwort
  2. Medical Education
    Typ
    Schlagwort
  3. Technology
    Typ
    Schlagwort
  4. Ethics
    Typ
    Schlagwort
Subject categories of the Deutsche Nationalbibliografie:
610 Medical sciences Medicine
Hosting institution:
Faculty of Medicine, Essen University Hospital, Institute for Artificial Intelligence in Medicine (IKIM)
funding:

We acknowledge support by the Open Access Publication Fund of the University of Duisburg-Essen.

Open Access funding enabled and organized by Projekt DEAL.

Info on primary publication:

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). https://doi.org/10.1186/s12909-024-06048-z

Published: 07 October 2024

version identification:

Version of Record / Verlagsversion

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