人工智能语言模型提高了烧伤信息的可读性,提高了急救信息
1Department of Burns and Plastic Surgery, Buckinghamshire Healthcare NHS Trust, Buckinghamshire, UK.
概括
人工智能 (AI) 大型语言模型可以有效地提高烧伤急救信息的可读性. 使用人工智能重写患者教育材料显著增强了理解力,使关键健康指导更容易获得.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 卫生识字 卫生识字
背景情况:
- 关于烧伤急救的患者教育材料 (PEM) 往往缺乏最佳的可读性.
- 改善健康信息的可访问性对于有效的公共卫生沟通至关重要.
研究的目的:
- 评估人工智能大型语言模型在提高烧伤急救信息可读性方面的有效性.
- 确定AI是否可以调整现有内容以满足推的识字水平.
主要方法:
- 人工智能语言模型 (ChatGPT-3) 被用来重写顶级的英语燃烧急救网页的内容.
- 使用五种经过验证的工具评估可读性,目标是11岁的读写能力水平.
- 原始和人工智能修改材料使用统计分析进行了比较.
主要成果:
- 最初,只有4%的材料达到目标可读性水平;中位数为6.9.
- 在人工智能修改后,18%的材料达到目标可读性水平,平均分数为6.
- 人工智能重写显著改善了所有可读性得分 (p < .001).
结论:
- 人工智能大型语言模型是改善健康信息可读性的可行和有效工具.
- 人工智能驱动的内容修改可以使关键烧伤急救指南更易于理解和公众可访问.
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