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Sholem Hack¹, Shibli Alsleibi^2,3, Naseem Saleh^2,3

¹St. Georges University London School of Medicine, Program Delivered by University of Nicosia at The Chaim Sheba Medical Center, Ramat Gan, Israel. sholemhack1@gmail.com.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery

|April 30, 2025

概括

大型语言模型 (LLM) 是可靠和准确的,用于在部质量上的患者教育. 然而,它们应该补充,而不是取代专业的医疗建议,因为遵循指导方针的变化.

科学领域:

人工智能在医学中的应用
医疗信息学医疗信息学
耳鼻喉科耳鼻喉科耳鼻喉科

背景情况:

患者教育对于管理成人部质量至关重要.
大型语言模型 (LLM) 正在成为传播健康信息的潜在工具.
对特定的医疗查询来说,评估LLM的准确性和可靠性至关重要.

研究的目的:

评估LLMs在响应有关成人部质量的患者常见问题时的可靠性和准确性.
为了比较不同LLM平台 (ChatGPT,Claude,Gemini) 在提供医疗信息方面的表现.
根据既定的医疗标准来评估LLM反应.

主要方法:

关于成人部质量的24个患者问题被提出给ChatGPT,Claude和Gemini.
五位耳鼻喉科医生使用包括准确性,广泛性和遵守指南在内的标准审查了这些反应.
使用了统计分析,包括费舍尔的精确测试和弗莱斯的卡帕.

主要成果:

所有的LLM都显示出高可靠性 (91.7-100%).
付费GPT和Gemini实现了最高的准确性 (95.8%),而扩展度则差异很大.
在GPT模型中,指南引用率最高 (50%),误导性信息不常见 (0-16.7%).

结论:

在部质量方面,LLM显示出高可靠性和准确性,用于患者教育.
付费的LLM版本提供了稍微更好的性能.
法律学士可以作为有价值的教育辅助,但由于偶尔的错误信息和可变的准则遵守,需要仔细监督.

关键词:

美国耳鼻喉学会 - 头部手术人工智能的人工智能是人工智能.聊天GPT 聊天GPT 在线聊天大型语言模型.子质量子质量患者教育患者教育

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