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对五种主要语言模型对肝癌综合治疗的比较研究

Deyuan Zhong¹, Yuxin Liang¹, Hong-Tao Yan¹

¹Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.

Journal of hepatocellular carcinoma

|August 27, 2025

概括

大型语言模型 (LLM) 在肝癌查询中表现不同. GPT-4和Kimi是有前途的,但复杂推理的局限性需要在临床使用之前进行特定领域的优化.

科学领域:

医学的人工智能
癌症学
肝胆道疾病

背景情况:

大型语言模型 (LLM) 在医疗保健中越来越多地被采用.
它们在肝癌等专门的临床领域的可靠性是不确定的.
由于肝癌的复杂性, 人工智能应用面临着独特的挑战.

研究的目的:

评估五种主流LLM的可理解性和临床适用性.
评估与肝癌相关的临床问题.
确定目前在瘤学中的LLM的优点和弱点.

主要方法:

开发了90个标准化肝癌管理问题.
由肝胆专家盲目评估了五种LLM (GPT-4,Gemini,Copilot,Kimi,Ernie Bot).
使用预先定义的标准,对可理解性和临床适用性进行评分.

主要成果:

基米 (68%) 和GPT-4 (62%) 呈现出最高的完全适用性反应.
可理解性很高 (Kimi,Ernie Bot>98%),但指南一致性不一致.
与常识问题相比,LLM在复杂的专业问题上扎.

结论:

在肝癌临床查询中,LLM表现不同.
GPT-4和Kimi显示出临床应用的潜力.
针对特定领域的优化对于将LLM整合到肝癌治疗中至关重要,特别是对于复杂的决策.

关键词:

聊天GPT 临床适用性大型语言模型肝癌肝癌肝癌医疗聊天机器人

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