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医学领域的大型语言模型:潜力与陷阱:一篇叙事性综述。

Large Language Models in Medicine: The Potentials and Pitfalls : A Narrative Review.

机构信息

Department of Dermatology and Department of Biomedical Data Science, Stanford University, Stanford, California (J.A.O., R.D.).

Department of Dermatology, Stanford University, Stanford, California (H.G., S.J.R.).

出版信息

Ann Intern Med. 2024 Feb;177(2):210-220. doi: 10.7326/M23-2772. Epub 2024 Jan 30.

Abstract

Large language models (LLMs) are artificial intelligence models trained on vast text data to generate humanlike outputs. They have been applied to various tasks in health care, ranging from answering medical examination questions to generating clinical reports. With increasing institutional partnerships between companies producing LLMs and health systems, the real-world clinical application of these models is nearing realization. As these models gain traction, health care practitioners must understand what LLMs are, their development, their current and potential applications, and the associated pitfalls in a medical setting. This review, coupled with a tutorial, provides a comprehensive yet accessible overview of these areas with the aim of familiarizing health care professionals with the rapidly changing landscape of LLMs in medicine. Furthermore, the authors highlight active research areas in the field that promise to improve LLMs' usability in health care contexts.

摘要

大型语言模型(LLMs)是基于大量文本数据训练的人工智能模型,能够生成类似人类的输出。它们已被应用于医疗保健的各种任务,从回答医学考试问题到生成临床报告。随着生产 LLM 的公司与医疗系统之间的机构合作不断增加,这些模型在现实世界中的临床应用即将实现。随着这些模型的普及,医疗保健从业者必须了解 LLM 是什么、它们的发展、它们当前和潜在的应用以及在医疗环境中存在的相关陷阱。本综述结合教程,全面而又易于理解地介绍了这些领域,旨在使医疗保健专业人员熟悉医学领域中 LLM 的快速变化。此外,作者还强调了该领域的活跃研究领域,这些领域有望提高 LLM 在医疗保健环境中的可用性。

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