用FHIR+RAG构建医疗决策支持系统，提升临床指南应用效率
FHIR-RAG-MEDS: Integrating HL7 FHIR with Retrieval-Augmented Large Language Models for Enhanced Medical Decision Support
- 将HL7 FHIR标准与RAG技术结合，实现医疗数据智能检索
- 支持基于证据的个性化临床决策，提升诊疗建议精准度
- 适合医疗AI研发者和医院信息化团队参考
本研究提出FHIR-RAG-MEDS系统，旨在将健康水平7快速医疗互操作资源（HL7 FHIR）与基于检索增强生成（RAG）的技术相结合，以改进基于循证临床指南的个性化医疗决策支持。在医疗决策支持系统不断演进的背景下，整合RAG与HL7 FHIR等先进技术可显著提升临床决策质量。尽管这些技术具有巨大潜力，但其在实际应用中的融合研究仍较为有限。
原文摘要 · Abstract (English)
In this study, we propose FHIR-RAG-MEDS system that aims to integrate Health Level 7 Fast Healthcare Interoperability Resources (HL7 FHIR) with a Retrieval-Augmented Generation (RAG)-based system to improve personalized medical decision support on evidence-based clinical guidelines, emphasizing the need for research in practical applications. In the evolving landscape of medical decision support systems, integrating advanced technologies such as RAG and HL7 FHIR can significantly enhance clinical decision-making processes. Despite the potential of these technologies, there is limited research on their integration in practical applications.
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