语音响应分析代理 (VERAA):利用大型语言模型在SDoH调查中映射语音响应
medRxiv : the preprint server for health sciences
|October 9, 2023
概括
本研究引入了一种多语言的对话代理来收集健康的社会决定因素 (SDoH) 数据,解决电子健康记录 (EHR) 中的缺失问题和语言障碍,以获得更好的健康见解.
科学领域:
- 医疗信息学 医疗信息学
- 自然语言处理自然语言处理.
- 公共卫生 公共卫生
背景情况:
- 健康的社会决定因素 (SDoH) 显著影响健康结果,但在电子健康记录 (EHR) 中经常缺失.
- 有限的英语水平在患者和医疗保健提供者之间造成了沟通障碍,阻碍了全面的SDoH数据收集.
研究的目的:
- 设计和开发一个多语言对话代理,以在医疗保健环境中有效采集SDoH数据.
- 克服与缺乏SDoH数据和患者沟通中的语言障碍相关的挑战.
主要方法:
- 开发了一种多语言对话代理来进行SDoH调查.
- 代理人在患者的母语中与患者互动,将响应翻译成英语,并使用大型语言模型 (LLM) 将响应映射到结构化SDoH调查数据上.
- 该系统旨在在医院或家庭环境中提供灵活性.
主要成果:
- 会话代理成功地通过多语言调查收集SDoH数据.
- 患者的自由文本答案被转化为结构化数据,丰富SDoH信息.
- 该LLM有效地映射了对标准化调查选项的翻译响应.
结论:
- 这种新的方法促进了更具包容性和全面的SDoH数据收集.
- 实现更丰富的SDoH数据丰富,以改善健康结果预测和干预措施.
- 代表了利用技术促进健康公平和数据驱动医疗保健的重大进步.
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