谷歌博士对ChatGPT博士:评估人工智能产生的关于尾炎的医疗信息的内容和质量
Yazid K Ghanem1,2, Armaun D Rouhi3, Ammr Al-Houssan4
1Department of Surgery, Cooper University Hospital, 3 Cooper Plaza, Suite 411, Camden, NJ, 08103, USA. ghanem-yazidkhalilmo@cooperhealth.edu.
生成型人工智能聊天机器人提供了关于尾炎的高质量信息,但往往缺乏可验证的来源,并且难以阅读. 需要进一步开发以提高患者的准确性和可访问性.
科学领域:
- 人工智能在医学中的应用
- 医疗信息学 医疗信息学
- 患者教育 患者教育
背景情况:
- 生成性AI聊天机器人越来越多地被视为在线医疗信息的来源.
- 现有的在线患者健康信息在质量和可读性方面各不相同.
- 本研究评估了人工智能生成的关于急性尾炎的内容.
研究的目的:
- 评估人工智能生成的关于急性尾炎的医疗信息的内容质量.
- 评估人工智能生成的医疗信息的可读性.
- 为了比较不同AI聊天机器人在提供医疗信息方面的表现.
主要方法:
- 四个人工智能聊天机器人 (ChatGPT-3.5,ChatGPT-4,Bard,Claude-2) 产生了有关尾炎的信息.
- 使用修改后的DISCERN工具 (16-80分) 评估内容质量.
- 使用Flesch阅读易度 (FRE) 和Flesch-Kincaid等级水平 (FKGL) 测量可读性.
主要成果:
- 人工智能聊天机器人取得了良好的质量评分 (51.3-62.3/80),具有相当大的评级者间可靠性.
- 巴德提供了可验证的消息来源;克劳德-2捏造了消息来源.
- 可读性是具有挑战性的,FKGL分数表明大学水平的阅读困难.
结论:
- 人工智能产生的尾炎信息显示出患者教育的潜力,但需要验证来源.
- 可读性水平超过了公众可访问性建议.
- 生成型人工智能平台需要改进,以确保可靠的患者参与医疗主题.
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