生成型人工智能可以提高放射学实践中患者教育材料的可读性吗?
1The University of Texas at Austin, Dell Medical School, Department of Diagnostic Medicine, Austin, TX, USA.
Clinical radiology
|September 12, 2024
概括
像ChatGPT-4和Google Gemini这样的生成性AI工具显著提高了患者教育材料的可读性,达到六年级的水平. 放射科医生证实了AI简化的文本是适当和相关的,突出了AI.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 提高健康素养 提高健康素养
背景情况:
- 患者教育材料往往超过推的阅读水平,阻碍了理解.
- 简化复杂的医疗信息对于有效的患者参与和遵守至关重要.
- 生成型人工智能为改善健康信息的可访问性提供了一个潜在的解决方案.
研究的目的:
- 评估现有的患者教育材料的可读性.
- 评估生成AI (ChatGPT-4,谷歌双子) 在将这些材料简化到六年级阅读水平的有效性.
- 在可读性,信息保留和专家验证的质量方面比较不同AI模型的性能.
主要方法:
- 选择了七个放射病患者教育文件.
- 聊天GPT-4和谷歌双子将文档重新编制为六年级的阅读水平.
- 计算了平均阅读水平 (ARL),比例词数 (PWC) 变化和信息保留.
- 三名放射科医生使用利克尔特尺度评估人工智能产生的内容的适当性,相关性和清晰度.
主要成果:
- 原始材料的ARL为11.72;人工智能显著降低了这一点 (ChatGPT:7.32,双子座:6.55).
- 聊天GPT减少了15%的字数 (95%保留了>75%的信息);双胞胎减少了33% (68%保留了>75%的信息).
- 与双子座相比,ChatGPT的输出在适当性 (95%与57%相比),清晰性 (92%与67%相比) 和相关性 (95%与76%相比) 方面获得了更高的评分.
结论:
- 生成型人工智能显著提高了患者教育材料的可读性,符合推的指南.
- 人工智能简化的文本被专家放射科医生认为是适当和相关的.
- 生成型人工智能工具对提高健康素养充满希望,持续的专家审查对于准确性至关重要.
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