Scholarlink

This paper details a technical plan for building a clinical case database for Traditional Chinese Medicine (TCM) using web scraping. Leveraging multiple platforms, including 360doc, we gathered over 5,000 TCM clinical cases, performed data cleaning, and structured the dataset with crucial fields such as patient details, pathogenesis, syndromes, and annotations. Using the \(Baidu\_ERNIE\_Speed\_128K\) API, we removed redundant information and generated the final answers through the DeepSeekv2 API, outputting results in standard JSON format. We optimized data recall with Retrieval Augmented Generation(RAG) and rerank techniques during retrieval and developed a hybrid matching scheme. By combining two-stage retrieval method with keyword matching via Jieba, we significantly enhanced the accuracy of model outputs.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Traditional Chinese Medicine Case Analysis System for High-Level Semantic Abstraction: Optimized with Prompt and RAG

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Peng Xu,
  • Hongjin Wu,
  • Jinle Wang,
  • Rongjia Lin,
  • Liwei Tan

摘要

This paper details a technical plan for building a clinical case database for Traditional Chinese Medicine (TCM) using web scraping. Leveraging multiple platforms, including 360doc, we gathered over 5,000 TCM clinical cases, performed data cleaning, and structured the dataset with crucial fields such as patient details, pathogenesis, syndromes, and annotations. Using the \(Baidu\_ERNIE\_Speed\_128K\) API, we removed redundant information and generated the final answers through the DeepSeekv2 API, outputting results in standard JSON format. We optimized data recall with Retrieval Augmented Generation(RAG) and rerank techniques during retrieval and developed a hybrid matching scheme. By combining two-stage retrieval method with keyword matching via Jieba, we significantly enhanced the accuracy of model outputs.