眼睛在文本上:评估人工智能的可读性和眼科医生对患者手术查询的反应
Sai S Kurapati1, Derek J Barnett2, Antonio Yaghy3
1Department of Ophthalmology, Penn State College of Medicine, Hershey, Pennsylvania, USA, skurapati1@pennstatehealth.psu.edu.
概括
对眼科手术的生成人工智能 (AI) 响应比眼科医生写的响应要难读. 这两个来源都超过了推的健康信息可读性水平,人工智能对患者的理解构成了更大的挑战.
科学领域:
- 眼科医生 眼科 眼科
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 生成型人工智能,如GPT-4,提供快速的健康信息传播.
- 面向患者的人工智能生成的健康内容可读性在很大程度上未经检查.
- 眼科医生撰写的内容作为健康信息清晰度的基准.
研究的目的:
- 为了比较GPT-4生成的响应的可读性与眼科医生对眼科手术患者查询的书面响应.
- 评估人工智能生成的健康信息是否适合患者理解.
- 确定人工智能和人类专家之间在健康信息可访问性方面的潜在差异.
主要方法:
- 一项回顾性横截面研究分析了200个关于眼科手术的患者问题.
- 生成了GPT-4响应,并与EyeSmart平台上的眼科医生撰写的回复进行了比较.
- 采用了六个经过验证的可读性指标 (例如,弗莱什金凯德等级水平,炮雾得分).
主要成果:
- 在GPT-4反应中,复杂词的比例较高 (24.42%) 与眼科医生 (17.76%) 相比.
- 在所有评估的可读性指标 (p < 0.05) 中,人工智能生成的内容需要更高的分级水平来理解.
- 无论是GPT-4还是眼科医生的反应都需要12年级的阅读水平,超过NIH的建议.
结论:
- 由GPT-4生成的眼科手术信息比专家撰写的内容难以阅读.
- 人工智能和人类专家的反应都超过了推的6-7年级健康信息阅读水平.
- 提高人工智能驱动的健康信息可访问性对于患者教育和资源设计至关重要.
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