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Qiting Wang¹, Huiru Zou², Haobin Zhang²

¹School of Public Health Guangdong Pharmaceutical University Guangzhou China.

Health care science

|March 2, 2026

概括

大型语言模型 (LLM) 显示出很大的医疗保健潜力,但需要严格的评估. 本研究提出了一个三维框架来评估LLM医疗能力,涵盖知识,实践和道德.

科学领域:

医疗信息学医疗信息学
医疗保健中的人工智能
临床评估临床评估

背景情况:

大型语言模型 (LLM) 显示了改变医疗保健应用的巨大潜力.
医疗实践的关键性质需要对LLM医疗能力进行彻底评估.
现有的LLM评估方法缺乏临床准备的系统方法.

研究的目的:

对评估LLM医疗能力的方法和基准进行全面审查.
为医疗保健中LLM评估提出一个结构化的三维框架.
为未来的LLM开发和医疗整合标准化提供见解.

主要方法:

对当前的LLM评估实践进行系统审查.
对医学知识,临床实践和道德安全领域的评估进行分析.
将临床医师能力评估框架集成到LLM评估中.

主要成果:

确定了LLM医学能力评估的既定方法和基准.
开发了一个三维框架,将评估分类为医学知识,临床实践和道德安全.
突出了当前评估实践和拟议的标准化协议中的差距.

结论:

结构化,三维框架对于严格评估LLM医学能力至关重要.
标准化协议对于安全有效地将LLMs纳入临床实践至关重要.
未来的研究应该专注于改进评估指标,并确保在医疗保健中道德地部署LLM.

关键词:

一个基准的基准指标.大型语言模型医疗能力的医疗能力.

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