聊天GPT对医疗决策,偏见和公平的影响:对临床医生评估临床标签的随机研究
Ethan Goh1,2, Bryan Bunning1, Elaine Khoong3
1Stanford Biomedical Informatics Research, Stanford University, Stanford, CA.
medRxiv : the preprint server for health sciences
|December 11, 2023
概括
像ChatGPT这样的生成人工智能提高了医生在诊断胸痛时的准确性,而不会增加偏见. 大多数医生认为,大型语言模型将在未来的临床决策中发挥至关重要的作用.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床决策支持系统 临床决策支持系统
背景情况:
- 医生的决策准确性对于患者的结果至关重要.
- 医疗保健中的潜在偏见可能会影响临床判断.
- 生成型人工智能为医疗应用提供了新的工具.
研究的目的:
- 评估大语言模型 (LLM) 对医生决策准确性的影响.
- 评估人工智能协助是否引入或加剧种族或性别偏见.
- 测量医生对AI在临床实践中的作用的看法.
主要方法:
- 一个随机的,干预前后研究设计.
- 50名医生审查了临床记录并回答了问题.
- 在接受AI (ChatGPT+ GPT4) 建议后,医生重新考虑了决策.
主要成果:
- 人工智能协助显著提高了临床决策准确性.
- 没有观察到种族或性别偏见的引入或恶化.
- 医生表示愿意根据AI输入改变最初的印象.
结论:
- 大型语言模型可以在临床场景中提高诊断准确性.
- 人工智能工具显示出无偏见的临床决策支持的潜力.
- 医生预计LLM工具在医疗保健中将在未来发挥重要作用.
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