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评估聊天GPT和DeepSeek之间大型语言模型在双语个体喘教育中的作用:比较研究

Yaxin Liu^1,2,3, Fangfei Yu¹, Xiaofei Zhang¹

¹Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150081, China, +86 138 3612 4743.

JMIR medical informatics

|August 13, 2025

概括

这项研究比较了两种AI大语言模型 (LLM) 用于双语喘教育. DeepSeek-v3在临床完整性方面表现出色,而ChatGPT-4o提供了更高的清晰度,有助于患者自我管理.

科学领域:

医疗保健中的人工智能
医疗教育技术技术医学教育
数字健康数字健康

背景情况:

喘管理需要持续的患者教育,特别是对于不同的语言群体.
大型语言模型 (LLM) 显示出改善健康沟通的希望.
有限的比较研究存在于LLMs的疾病特异性,双语患者教育.

研究的目的:

评估和比较ChatGPT-4o和DeepSeek-v3用于双语 (英语/中文) 喘患者教育.
根据准确性,完整性,临床相关性和语言适应性来评估绩效.
在这种情况下,确定每个LLM的优点和弱点.

主要方法:

在8个领域收集了53个与喘相关的患者问题.
用英语和中文向ChatGPT-4o和DeepSeek-v3.3发送的问题.
通过盲目的呼吸系统临床医生使用7D临床质量框架评估反应.

主要成果:

这两个LLM都制作了高质量的双语喘教育内容.
在内容完整性和流通性方面,DeepSeek-v3超过了ChatGPT-4o.
聊天GPT-4o在回复中表现出更高的清晰度和可访问性.

结论:

聊天GPT-4o和DeepSeek-v3为双语喘教育提供了互补的好处.
对于详细的临床信息,DeepSeek-v3更强大;对于一般理解,ChatGPT-4o更强大.
临床治疗方法可以补充患者的自我管理,但需要人类监督以确保准确性和安全性.

关键词:

患者教育患者教育聊天GPT 聊天在GPT 聊天在DeepSeek搜索中深入搜索.喘喘是一种跨语言研究研究.

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