Application of Large Language Model Technology Based on Retrieval-Augmented Generation in Hospital IT Operations and Maintenance
Objective To address the complexities and retrieval difficulties of existing knowledge base systems,we aim to develop an IT operations and maintenance knowledge base Q&A system based on Retrieval-Augmented Generation (RAG) enhanced large language model technology. Methods By utilizing RAG technology,integrating data from traditional knowledge base systems,and incorporating various forms of data such as images and operation documents,we have constructed a comprehensive and highly practical knowledge base Q&A system. Results Since the system's launch,its usage has steadily increased,effectively improving clinical satisfaction and reducing the workload of the IT department. Conclusion The RAG-enhanced large language model technology resolves the complexity and retrieval difficulties issues of traditional knowledge bases,significantly improving clinical staff satisfaction with IT operational and maintenance services and enhancing the overall level of hospital IT operations and maintenance.
retrieval-augmented generationlarge language modelshospital IT operations and maintenanceknowledge base
万方数据
维普
