[1]LI Dawei,CHEN Weina,SHAN Xiaoli.Research on the Design and Application of Blood Donation Consultation Service System[J].Chinese Health Quality Management,2026,33(3):67-70.[doi:10.13912/j.cnki.chqm.2026.33.3.15]
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Research on the Design and Application of Blood Donation Consultation Service System
Chinese Health Quality Management[ISSN 1006-7515/CN CN 61-1283/R] Volume:
33
Number of periods:
2026年3期
Page number:
67-70
Column:
血液质量
Public date:
2026-03-15
- Title:
- Research on the Design and Application of Blood Donation Consultation Service System
- Keywords:
- Large Language Model; Retrieval-Augmented Generation Technology; Voluntary Blood Donation; Blood Donation Consultation; Blood Donation Service
- CLC:
- R197.6；R331.1
- DOI:
- 10.13912/j.cnki.chqm.2026.33.3.15
- Abstract:
- ObjectiveTo construct a blood donation consultation service system that enables self-service answers to standardized questions.MethodsBased on retrieval-augmented generation technology, an dedicated knowledge base for voluntary blood donation was established. Leveraging the natural language dialogue capabilities of large language models, a blood donation consultation service system was developed.ResultsSince the system’s operation for four months, the volume of inquiries regarding blood fee reimbursement and blood donation knowledge has decreased by 5.37% and 2.73%, respectively, compared to the same period. Additionally, inquiries about commendation policies have decreased by 28.89% compared to the previous commendation year.Conclusion The blood donation consultation service system, constructed based on large language models and retrieval-augmented generation technology, can effectively alleviate the workload of human customer service representatives and holds significant potential for broader application and promotion.
- References:
- ［1］裘君娜，孔长虹，金立明，等.献血咨询管理系统构建及应用［J］.中国卫生质量管理，2022，29（7）：94-96.［2］王 亮.检索增强生成（RAG）驱动的知识服务：原理、范式及评估［J］.科技与出版，2025（4）：37-46.［3］李大玮，陈委娜，刘 鹏，等.基于智慧城市概念模型的智慧血液网建设与应用［J］.中国卫生质量管理，2023，30（1）：80-83.［4］高雅奇.基于大语言模型和RAG技术的高校知识库智能问答系统构建与评价［J］.电脑知识与技术，2024，20（29）：18-20，38.［5］文 森，钱 力，胡懋地，等.基于大语言模型的问答技术研究进展综述［J］.数据分析与知识发现，2024，8（6）：16-29.［6］吴 璇，付 涛.检索增强生成技术研究综述［J］.计算机工程与应用，2025,61（20）：19-35.［7］姚 畅，王贵宣，相 鹏，等.医学大模型与多模态数据融合在智慧医疗中的机会、挑战与实践［J］.中国卫生信息管理杂志，2025，22（2）：171-178.［8］田雪晴，李泉江，游 茂，等.我国医疗机构大语言模型建设现状调查与分析［J］.中国卫生信息管理杂志，2025，22（1）：38-44.［9］BEDI P，THUKRAL A，DHIMAN S.XLR-KGDD：leveraging LLM and RAG for knowledge graph-based explainable disease diagnosis using multimodal clinical information［J］.Knowl Inf Syst，2025（prepublish）：1-21.［10］曹书林，史佳欣，侯 磊，等.知识库问答研究进展与展望［J］.计算机学报，2023，46（3）：512-539.［11］贺 李，刘兴红，贾鹏宇.基于RAG架构的智能知识库设计与应用研究［J］.信息记录材料，2025，26（6）：127-129.［12］富国瑞，王平利，王一展，等.基于大语言模型的高校图书馆智能参考咨询服务构建与应用研究——以山东大学图书馆为例［J］.图书馆杂志，2025,44(12):31-40.
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Last Update:
2026-03-15