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测试人工智能聊天机器人:在基底细胞癌的背景下对大型语言模型性能进行比较分析

Vinzent K Ortner^1,2, Heather C Lent³, Katrine E Karmisholt^1,4

¹Department of Dermatology, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark.

Experimental dermatology

|November 11, 2025

概括

与Gemini和Copilot相比,ChatGPT 4.0在指导基底细胞癌治疗方面表现出卓越的事实准确性和临床实用性. 皮肤科医生评估对于评估皮肤瘤学中的大型语言模型至关重要.

科学领域:

皮肤瘤学皮肤瘤学
人工智能在医学中的应用
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) 越来越多地被用于瘤学的应用.
在指导特定皮肤癌,如基底细胞癌 (BCC) 的临床管理LLMs的实用性需要严格的评估.
评估LLM绩效需要对不同模型进行比较和专家的人类判断.

研究的目的:

为了比较不同大型语言模型 (LLM) 在为基底细胞癌 (BCC) 治疗提供指导的性能.
根据事实准确性,简洁性,全面性和专家偏好来评估LLM响应.
量化评估LLM答案之间的词汇和语义相似性.

主要方法:

四位作者为基底细胞癌 (BCC) 提出了24个临床管理问题.
来自三个LLM (Gemini,Copilot,ChatGPT 4.0) 的答案是盲目的,并由九名皮肤瘤学家对准确性,简洁性,全面性和偏好进行评估.
使用词汇和语义相似度指标对另外三个LLM进行了LLM响应的定量比较 (ChatGPT 3.5,ChatGPT 4o,Claude).

主要成果:

聊天GPT 4.0 显示了最高的事实准确度 (87.5%),其次是双子座 (50%) 和 Copilot (25%).
聊天GPT 4.0还在简洁性 (54.2%) 和全面性 (62.5%) 中领先,其他模型得分明显低.
皮肤瘤学家在54.2%的病例中更喜欢ChatGPT 4.0响应;语义相似性中等 (0.60-0.70),而词汇相似性低 (0.07-0.10).

结论:

目前,ChatGPT 4.0在基底细胞癌 (BCC) 治疗指南的准确性和临床实用性方面优于Gemini和Copilot.
在专家皮肤瘤学建议有限的情况下,LLM显示出支持临床医生的潜力.
单纯的定量指标是不够的;专家皮肤科医生评估对于确定临床相关的LLM绩效至关重要.

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