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Large language models in medicine: the potentials and pitfalls

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arxiv 2309.00087 v1 pith:N4SAPKHP submitted 2023-08-31 cs.CL cs.AIcs.CY

classification cs.CLcs.AIcs.CY
keywords healthcarellmsmedicinemodelsappliedlanguagelargepitfalls
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Large language models (LLMs) have been applied to tasks in healthcare, ranging from medical exam questions to responding to patient questions. With increasing institutional partnerships between companies producing LLMs and healthcare systems, real world clinical application is coming closer to reality. As these models gain traction, it is essential for healthcare practitioners to understand what LLMs are, their development, their current and potential applications, and the associated pitfalls when utilized in medicine. This review and accompanying tutorial aim to give an overview of these topics to aid healthcare practitioners in understanding the rapidly changing landscape of LLMs as applied to medicine.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Strategic Prompting for Conversational Tasks: A Comparative Analysis of Large Language Models Across Diverse Conversational Tasks

    cs.CL 2024-11 reject novelty 3.0 of 10

    No single open-source LLM among Llama, OPT, Falcon, Alpaca, and MPT performs best across reservation, empathy, counseling, persuasion, and negotiation tasks.

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