使用ChatGPT提高耳鼻喉科患者教育材料的可读性和理解水平
Allison D Oliva1, Luke J Pasick1, Michael E Hoffer1
1Department of Otolaryngology-Head and Neck Surgery, University of Miami Miller School of Medicine, United States of America.
American journal of otolaryngology
|August 28, 2024
概括
大型语言模型可以评估和简化耳鼻喉科患者教育材料,以提高可读性. 人工智能工具在使复杂的医疗信息更容易获得患者方面表现有前途.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 卫生识字 卫生识字
背景情况:
- 耳鼻喉科的患者教育材料往往超过了推的阅读水平.
- 提高健康素养对于患者的理解和参与至关重要.
研究的目的:
- 评估大型语言模型 (LLM) 在评估和提高耳鼻喉科患者教育材料的可读性方面的实用性.
- 为了确定LLM生成的翻译是否符合6年级和8年级推的阅读水平.
主要方法:
- 美国喉科协会 (ALA) 和美国耳鼻喉科-头手术学会 (AAO-HNS) 的患者教育材料的横截面分析.
- 使用ChatGPT (3.5版本) 和微软Word计算Flesch阅读方便 (FRE) 和Flesch-Kincaid (FK) 等级.
- 使用FRE和FK分数,将原始材料与ChatGPT翻译版本进行比较 (5年级级级别的提示).
主要成果:
- 在LLM翻译后,FRE分数和FK等级水平的显著改善被观察到 (p < 0.001).
- 微软Word也显示了通过ChatGPT翻译的AAO-HNS材料的改进,但不是单个主题.
- 与Word相比,ChatGPT倾向于夸大可读性得分的改善.
结论:
- 耳鼻喉科患者教育材料经常以太高的阅读水平写作,这对于一般患者来说太高了.
- 人工智能,特别是LLM,为简化医疗内容和提高患者可访问性提供了潜在的解决方案.
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