基于检索增强生成的电子医疗记录聊天机器人系统的开发和评估
Namrye Son1, Inchul Kang2, Inhu Kim2
1Software-Centered University Project Group, Chonnam National University, Gwangju, Korea.
Healthcare informatics research
|August 21, 2025
概括
这项研究开发了一种使用电子病历手册 (EMR) 的搜索增强型聊天机器人 (RAG),以改善医院的运作. 通过提供快速准确的信息检索, 该系统可增强行政工作流程和医疗保健服务.
科学领域:
- 卫生信息学
- 医疗保健中的人工智能
- 自然语言处理
背景情况:
- 医院运营面临管理效率和复杂电子病历 (EMR) 手册中的信息访问的挑战.
- 简化工作流程和加强医疗保健服务对于优化医院业绩至关重要.
研究的目的:
- 开发和评估基于搜索增强代 (RAG) 的聊天机器人系统,以优化医院运营.
- 利用EMR手册改善行政工作流程和医疗保健服务.
主要方法:
- 集成的微调多语言嵌入模型 (多语言-E5-Large,BGE-M3) 用于从EMR手册中索引和检索.
- 建立了5931个问题-文档对的数据集,经过专家验证.
- 使用对比学习进行微调,并使用太阳迷你聊天API生成韩语文本.
主要成果:
- 微调模型显示了显著的检索精度提高 (BGE-M3: 97.6%,多语言-E5-Large: 89.7%).
- 聊天机器人显示了低查询延迟 (<10 ms) 和高检索精度的操作EMR查询.
- 应用包括管理任务支持和账单流程优化,减少员工的工作量.
结论:
- 在医疗管理中,RAG聊天机器人有效地提高了EMR的可用性和运营效率.
- 建议进一步进行实践部署和纵向研究,以评估减少行政负担和改善工作流程.
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