大型语言模型和初级临床医生撰写的免费信件质量的比较:单盲研究
Joshua Yi Min Tung1,2, Sunil Ravinder Gill1, Gerald Gui Ren Sng2,3
1Department of Urology, Singapore General Hospital, Singapore, Singapore.
Journal of medical Internet research
|July 24, 2024
概括
GPT-4生成了与初级医生的质量相匹配的泌尿器科出院信,改善了没有幻觉的信息传递. 这表明大型语言模型是安全的临床文档工具.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床文档 临床文档
背景情况:
- 退院信对护理连续性至关重要,但耗时,经常被委托给初级医生.
- 现有的下放总结显示质量不足.
- 像GPT这样的大型语言模型 (LLM) 可以自动化文档,节省时间并确保一致性.
研究的目的:
- 评估GPT-4在向初级保健提供者生成泌尿病学出院信件方面的表现.
- 为了比较GPT-4产生的信件质量与初级临床医生写的信件.
主要方法:
- 虚构的泌尿外科门诊病例是用模拟的临床记录创建的.
- GPT-4使用安全性,内容和风格的特定提示生成放电信.
- 初级临床医生从相同的记录中起草了信件;一个盲目的初级保健医生小组评估了所有信件.
主要成果:
- 在信息提供方面,GPT-4显著超过了人类 (P=.03).
- 在GPT-4输出中没有观察到幻觉.
- 在清晰度, collegiality,简洁性,后续建议或整体满意度方面没有发现显著差异.
结论:
- GPT-4生产了与初级临床医生的同等质量的释放信,提供了增强的信息,没有幻觉.
- 在临床文档的安全和有效工具中,LLM显示出潜在的潜力,支持医疗保健专业人员.
关键词:
在这里,我们可以看到AIAIAI.聊天GPT 聊天 在GPT 聊天在法学士 (LLM) 课程中.人工智能的人工智能是人工智能.咨询说明 咨询说明护理的连续性 护理的连续性放电总结 放电总结 放电总结这是一个虚构的电子记录.年轻的临床医生.大型语言模型写信 写信 写信 写信 写信主要护理是一级医疗保健.推信是一个推信.模拟环境是一个模拟环境.一个单盲的.泌尿病学 泌尿病学 泌尿病学更多相关视频
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