一项跨部门研究,将人工智能生成的医学专业人员肺炎教育内容与UpToDate进行比较
Aarushi Grover1, Burhanuddin Kherodawala2, Neha Uppal3
1Internal Medicine, Sri Ramachandra Institute of Higher Education and Research, Chennai, IND.
Cureus
|November 10, 2025
概括
聊天GPT产生的肺炎内容比UpToDate更短,更密集,但可读性得分相似. 人工智能可能提供快速摘要,而UpToDate则为医学教育提供临床深度.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 临床信息资源 临床信息资源
背景情况:
- 准确的医学教育资源对于治疗肺炎的医疗保健专业人员至关重要.
- 资源必须与当前的临床指南保持一致,以改善诊断和患者的治疗结果.
研究的目的:
- 将人工智能生成的内容 (ChatGPT) 的可读性和特性与肺炎的可信临床资源 (UpToDate) 进行比较.
- 评估人工智能工具在复杂领域 (如肺炎治疗) 的医学教育中的适用性.
主要方法:
- 分析了来自ChatGPT和UpToDate的关于肺炎的内容.
- 使用Flesch-Kincaid阅读易度和等级水平指标来评估可读性.
- 进行了统计分析,在p < 0.05时设置了显著性.
主要成果:
- 聊天GPT的内容明显比UpToDate更短,更密集.
- 与UpToDate相比,ChatGPT的词汇表现更加复杂.
- 这两个来源都显示了可比的可读性得分.
结论:
- 聊天GPT可以为医学教育提供快速,可访问的摘要.
- UpToDate提供了更全面,临床基础的信息.
- 利用人工智能和传统资源的综合方法可以增强医学教育,等待临床准确性验证.
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