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Valentina Ignacia Alvarez-Silberberg^1,2, Camila Paz Alvarez-Silberberg², Cosimo Galletti³

¹Faculty of Dentistry, Universitat Internacional de Catalunya, Barcelona, 08195, Spain.

Scientific reports

|February 27, 2026

概括

四个大型语言模型 (LLM) 被测试用于解释口腔病理学. 聊天GPT o1-预览显示了最高的准确性和病理学家的同意,表明作为决策支持工具的潜力.

科学领域:

口腔病理学口腔病理学
医学中的人工智能
组织病理学解释解释

背景情况:

大型语言模型 (LLM) 在医疗应用中表现有前途.
解释口腔病变的组织病理学描述需要专门的专业知识.
在这种诊断背景下评估LLM绩效至关重要.

研究的目的:

评估四个基于LLM的聊天机器人作为口腔病变组织病理学解释的决策支持系统的性能.
为了比较不同LLM与专家病理学家诊断的诊断准确度和一致性.
分析影响LLM绩效的因素,如患者的年龄和性别.

主要方法:

四个LLM (ChatGPT-4.0,ChatGPT o1-预览,双子座,Meta AI) 解释了他的病理学描述.
结果 (主要解释和差异诊断) 与病理学家的共识参考诊断进行了比较.
统计分析包括弗里德曼测试,威尔科克森签名等级测试,科恩的 κ 和回归分析.

主要成果:

聊天GPT o1-预览获得了与病理学家的最高一致性 (68.6%) 和实质性协议 (κ=0.66).
同时,Meta AI也显示出相当大的同意率 (65.7%, κ=0.63),其次是ChatGPT-4.0 (59.8%, κ=0.57).
双子座表现出不良的一致性 (27.5%, κ=0.24);年龄的增加对大多数模型的性能略有降低.

结论:

聊天GPT o1-预览成为口腔组织病理学解释支持的表现最好的LLM.
法律法规显示出作为互补工具的潜力,但模型之间存在显著的变化.
用人监督的谨慎实施对于将LLM整合到组织病理学工作流程中至关重要.

关键词:

人工智能的人工智能是人工智能.聊天GPT 聊天在GPT 聊天聊天机器人聊天机器人双子座是一个双子座.大型语言模型.超级人工智能超级人工智能口腔和大面部病理学

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