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Artificial Intelligence in Healthcare and Education

Creation and Adoption of Large Language Models in Medicine

Nigam H. Shah, David A. Entwistle, Michael A. Pfeffer

Artificial Intelligence in Healthcare and EducationMachine Learning in HealthcareTopic Modeling
Published August 7, 2023Read PDF ↗View on arXiv ↗

Abstract

Importance: There is increased interest in and potential benefits from using large language models (LLMs) in medicine. However, by simply wondering how the LLMs and the applications powered by them will reshape medicine instead of getting actively involved, the agency in shaping how these tools can be used in medicine is lost. Observations: Applications powered by LLMs are increasingly used to perform medical tasks without the underlying language model being trained on medical records and without verifying their purported benefit in performing those tasks. Conclusions and Relevance: The creation and use of LLMs in medicine need to be actively shaped by provisioning relevant training data, specifying the desired benefits, and evaluating the benefits via testing in real-world deployments.

Sourced from arXiv · Updated September 2, 2026

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FAQ

Common questions

What is "Creation and Adoption of Large Language Models in Medicine" about?

Importance: There is increased interest in and potential benefits from using large language models (LLMs) in medicine. However, by simply wondering how the LLMs and the applications powered by them will reshape medicine instead of getting actively involved, the agency in shaping

Who wrote this paper?

Nigam H. Shah, David A. Entwistle, Michael A. Pfeffer

Where can I read the full paper?

The full text is available as a PDF on arXiv (linked above), published August 7, 2023.

Does this paper have a DOI?

Yes: https://doi.org/10.1001/jama.2023.14217.