实现公平的文档:评估ChatGPT在识别和重新表达电子健康记录中的污名化语言方面的作用
Zhihong Zhang1, Jihye Kim Scroggins2, Sarah Harkins3
1School of Nursing, Columbia University, New York, NY; Data Science Institute, Columbia University, New York, NY.
聊天GPT可以帮助减少电子健康记录 (EHR) 中的污名化语言. 虽然识别是不完美的,但人工智能辅助的重新表述有望改善临床笔记和患者关系.
科学领域:
- 自然语言处理自然语言处理.
- 临床信息学 临床信息学
- 健康 公平 卫生 公平
背景情况:
- 在电子健康记录 (EHR) 中对语言的污名化会对临床医生与患者的关系产生负面影响,并加剧健康差异.
- 临床文档中存在偏见的语言需要用于识别和减轻其策略.
研究的目的:
- 评估ChatGPT-4在临床笔记中识别和重新表达污名化语言方面的有效性.
- 评估AI在去污名化EHR内容的表现,同时保持临床准确性.
主要方法:
- 分析了140个临床笔记和150个城市医院的污名化例子.
- 使用ChatGPT-4来识别和重新表达污名化的内容.
- 通过精确度,回忆,F1分数和利克特尺度上的专家评分来评估性能.
主要成果:
- 聊天GPT-4显示了整体中等的识别性能 (微F1=0.51),但在特定类别的高性能 (微F1=0.69-0.91).
- 人工智能生成的重新表达得到了高专家评分,因为它消除了耻辱 (2.7),忠实 (2.8),简洁 (3.0) 和清晰 (3.0).
- 发现快速设计显著影响了ChatGPT的有效性.
结论:
- 聊天GPT显示了作为一个支持工具的潜力,用于实时识别和重新表达在电子人权书中的污名化语言.
- 有效的实施需要谨慎的及时工程和必要的人类监督,以解决自动识别的局限性.
- 人工智能辅助的脱污名化可以有助于更公平和尊重的临床文档.
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