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医学中的大型语言模型:潜力和陷:叙述审查

Jesutofunmi A Omiye¹, Haiwen Gui², Shawheen J Rezaei²

¹Department of Dermatology and Department of Biomedical Data Science, Stanford University, Stanford, California (J.A.O., R.D.).

Annals of internal medicine

|January 29, 2024

概括

大型语言模型 (LLM) 是人工智能工具,正在改变医疗保健. 本综述解释了LLM,其医疗用途以及医疗保健专业人员的潜在风险.

科学领域:

人工智能在医学中的应用
自然语言处理应用程序
临床决策支持系统临床决策支持系统

背景情况:

大型语言模型 (LLM) 是在广泛的文本数据上训练的高级AI.
士在医疗问题回答和报告生成等任务中表现出能力.
人工智能开发人员和卫生系统之间日益增长的合作表明,LLMs即将临床整合.

研究的目的:

为医疗保健从业人员提供对法学士的全面理解.
让专业人士熟悉LLM的开发,应用和医疗环境中的挑战.
突出新兴的研究,以提高LLM在医疗保健中的实用性.

主要方法:

关于医疗保健中LLM的当前文献的审查.
在教程式的解释LLM的概念和功能.
分析潜在的临床应用和相关风险.

主要成果:

在医疗保健中,LLM提供了多样化的应用,从行政任务到临床支持.
了解LLM的能力和局限性对于安全有效的实施至关重要.
积极的研究重点是提高法学士准确性,可解释性和道德考虑.

结论:

医疗保健专业人员需要对LLMs的基础知识来导航他们的整合.
该评论作为一个可访问的指南,用于医学AI不断发展的景观.
未来的研究方向旨在优化LLMs,以改善临床实践和患者的结果.

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