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病理学中的大型语言模型:对聊天GPT和巴德的比较研究,病理学实习生对多项选择题进行了比较

Wei Du¹, Xueting Jin¹, Jaryse Carol Harris¹

¹Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, United States of America.

Annals of diagnostic pathology

|November 8, 2024

概括

大型语言模型 (LLM) 在病理学中表现有前途. 在多选题问题上,ChatGPT显著优于Bard和实习生,显示出高准确性和一致性.

科学领域:

人工智能在医学中的应用
数字病理学数字病理学
医疗教育技术技术医学教育

背景情况:

大型语言模型 (LLM) 在各种医学领域都显示出潜力.
评估LLM在病理学等专业领域的表现对于理解它们的实用性至关重要.

研究的目的:

用多选题评估ChatGPT和Bard在病理学中的表现.
为了比较LLM的表现与病理学学员 (初级和高级) 的表现.
分析在多个测试会话中LLM响应的一致性和可变性.

主要方法:

使用了来自15个病理学子专业 (无图像) 的150个多选题.
在2023年6月至2024年1月期间,ChatGPT和Bard在三个会议中进行了测试.
答案与16名病理学实习生进行了比较;根据实习生的表现,问题根据难度分类.

主要成果:

聊天GPT的平均得分为82.2%,明显优于巴德 (49.5%) 和实习生 (初级:45.1%,高级:56.0%).
聊天GPT在难题 (63.4%-68.3%) 中表现出色,而在易题 (73.7%-100.0%) 中,实习生得分高.
聊天GPT显示出高的一致性 (80%-85%),而巴德显示出更大的变异性 (54%-61%).

结论:

法律学士,特别是ChatGPT,显示出病理学教育和实践的巨大潜力.
聊天GPT的卓越性能和一致性凸显了它在这个领域的先进能力.
持续的开发和基本的人类监督是必要的,以确保LLMs在病理学中的可靠临床整合.

关键词:

人工智能的人工智能是人工智能.巴尔德巴尔德巴尔德巴尔德是什么意思聊天GPT 聊天GPT 聊天这是一项比较性研究.不一致性不一致性不一致性大型语言模型.医学教育医学教育病理学病理学病理学居民居民的情况.

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