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评估通过ChatGPT-4及其相关插件生成的皮肤病患者信息传单的可读性
Dominik Todorov1, Jae Yong Park1, James Andrew Ng Hing Cheung1
1School of Medicine, Imperial College London, London, UK.
Skin health and disease
|March 24, 2025
概括
聊天GPT-4及其插件生成了患者信息传单 (PILs),这些传单并未始终达到为公众推的可读性水平. 虽然一些人工智能生成的PIL显示出比现有材料更好的可读性,但医疗保健专业人员的内容验证仍然至关重要.
科学领域:
- 卫生识字 卫生识字
- 医疗保健中的人工智能
- 医学写作 医学写作
背景情况:
- 很大一部分英国成年人 (43%) 难以获得标准的健康信息.
- 英国卫生教育建议,患者信息传单 (PIL) 应以11岁儿童的阅读水平编写.
研究的目的:
- 评估ChatGPT-4和皮肤病学插件能够创建可读的患者信息传单 (PILs) 的能力.
- 将人工智能生成的PIL与英国皮肤病学协会 (BAD) PIL的可读性进行比较.
主要方法:
- 聊天GPT-4和三个皮肤病插件为10种皮肤病产生了PIL.
- 使用简单测量Gobbledygook (SMOG),Flesch阅读易度测试 (FRET) 和Flesch-Kincaid等级水平测试 (FKGLT) 评估可读性.
- 一个单向ANOVA将人工智能生成的PIL与BAD PIL进行了比较.
主要成果:
- 人工智能生成的PIL并不始终达到目标可读性水平.
- 一些人工智能生成的PIL显示出比BAD PIL更好的可读性,对特定插件的SMOG和FKGLT得分有显著的改善.
- 聊天GPT-4生成的PIL有时缺乏在BAD PIL中发现的全面内容.
结论:
- 聊天GPT-4可以产生准确的皮肤学PIL,有时具有比BAD PIL更高的可读性.
- 然而,人工智能生成的PIL需要医疗保健专业人员对其准确性,完整性和公众理解性的验证.
- 目前的AI生成的PIL不能完全满足公众对易于理解的需求.
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