评估AI医疗文本的简化:可读性和内容忠实性
Bryce Picton1, Saman Andalib2, Aidin Spina2
1Department of Neurological Surgery, University of California, Irvine, Orange, CA, USA.
International journal of medical informatics
|December 12, 2024
概括
聊天GPT-4显著提高了医疗文本的可读性,使复杂的神经学信息可访问. 虽然内容完整性在很大程度上得到了维护,但对于人工智能生成的患者材料,专家验证仍然至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 科学沟通科学沟通
背景情况:
- 医学文献日益复杂,对患者的理解构成了挑战.
- 需要工具来提高医疗文本对大众的可读性.
- 神经学和神经外科摘要和患者教育材料 (PEMs) 通常包含复杂的术语.
研究的目的:
- 评估ChatGPT-4在简化医学文本方面的有效性.
- 评估简化神经学和神经外科摘要和PEM中的内容保存.
- 将隐性语义分析 (LSA) 与专家评估进行内容忠实性验证.
主要方法:
- 100个神经学/神经外科摘要和340个PEM被简化使用GPT-4.0到5年级的阅读水平.
- 弗莱什-金凯德等级水平 (FKGL) 和弗莱什阅读易度 (FKRE) 评分测量了可读性变化.
- 使用潜伏语义分析 (LSA) 和专家评价来评估内容的真实性.
主要成果:
- 可读性显著改善:FKGL从12年级降至5年级的摘要和13年级降至5年级的PEM (p < 0.001).
- LSA显示了高含量相似性 (摘要的平均值为0.746,PEM的平均值为0.953).
- 专家评估表明主题相似性很好 (摘要平均为0.775,PEM为0.715). 根据文本长度,LSA和专家相关性有所不同.
结论:
- GPT-4.0有效地提高了医疗文本的可读性,同时在很大程度上保留了内容.
- 在中等大小的文本中,LSA是评估内容忠实性的可靠工具.
- 专家验证对于人工智能生成的医疗内容至关重要,以确保准确性并解决自动评估的局限性,特别是对于更长的文档.
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