评估聊天GPT对心房的反应,以教育患者
Thomas J Lee1, Daniel J Campbell2, Abhinav K Rao3
1Department of Medicine, Rutgers University New Jersey Medical School, Newark, USA.
Cureus
|June 6, 2024
概括
聊天GPT为患者教育提供准确的心房动信息,并根据用户输入调整复杂性. 虽然它通常是正确的,但很少提供参考,强调需要在医疗保健中仔细整合人工智能.
科学领域:
- 医疗保健中的人工智能
- 医疗教育 技术 技术 医学教育
- 数字健康数字健康
背景情况:
- 一个流行的AI聊天机器人ChatGPT以对话流而闻名,但可以产生不准确的信息.
- 评估人工智能产生的内容的准确性和教育适用性对于患者的安全和理解至关重要.
- 心房动 (AF) 患者教育需要清晰,准确和易于获取的信息.
研究的目的:
- 评估ChatGPT对心房动 (AF) 患者教育问题的答案的准确性和可读性.
- 确定ChatGPT是否可以根据不同用户提示 (患者与医生) 量身定制响应复杂性.
- 评估人工智能生成的医疗信息的参考提供率.
主要方法:
- 聊天GPT得到了美国心脏协会关于AF的16个常见问题.
- 使用了四种提示形式:没有提示,患者友好,医生级,统计/参考.
- 对答案的准确性进行了评分 (不正确,部分正确,正确,完美) 和Flesch-Kincaid等级水平.
主要成果:
- 超过85%的ChatGPT回复被认为是正确的,只有1.6%是不正确的.
- 完美的答案 (正确的引用) 是罕见的 (4.7%),即使是特别要求的.
- 与其他形式相比,患者友好的提示导致平均成绩水平明显较低.
- 响应的准确性并没有显著不同于提示形式,但完美的响应率确实有所不同.
结论:
- 聊天GPT展示了作为医疗保健患者教育的准确信息资源的巨大潜力.
- 人工智能能够根据用户输入调整响应复杂性的能力是个性化教育的关键优势.
- 对人工智能的持续监测和进步是必要的,以最大限度地提高人工智能驱动的医疗保健教育的好处和降低风险.
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