Construction and Application of a Multicenter Traditional Chinese Medicine Proctology Disease Data Platform Based on Multimodal Large Models

ZHU Yuxin; ZHAO Liping; LU Jiafa; ZHU Huiting; YANG Xia; DU Lei; DING Kang

doi:10.13288/j.11-2166/r.2026.07.012

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Construction and Application of a Multicenter Traditional Chinese Medicine Proctology Disease Data Platform Based on Multimodal Large Models

更新时间：2026-04-01

- Construction and Application of a Multicenter Traditional Chinese Medicine Proctology Disease Data Platform Based on Multimodal Large Models
  增强出版
- Journal of Traditional Chinese Medicine Vol. 67, Issue 7, Pages: 770-775(2026)
- 作者机构：
  
  1.南京中医药大学附属南京市中医院，江苏省南京市秦淮区大明路157号，210022
  2.江苏省中医药管理局
  3.江苏省卫生健康信息中心
- 作者简介：
- 基金信息：
- DOI：10.13288/j.11-2166/r.2026.07.012
  CLC：
- Received：17 September 2025，
  
  Revised：2026-01-16，
  
  Published：02 April 2026
- 稿件说明：
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朱雨欣,赵莉萍,陆家发等.基于多模态大模型的多中心中医肛肠优势病种专病数据平台的构建与应用[J].中医杂志,2026,67(07):770-775.

ZHU Yuxin,ZHAO Liping,LU Jiafa,et al.Construction and Application of a Multicenter Traditional Chinese Medicine Proctology Disease Data Platform Based on Multimodal Large Models[J].Journal of Traditional Chinese Medicine,2026,67(07):770-775.
朱雨欣,赵莉萍,陆家发等.基于多模态大模型的多中心中医肛肠优势病种专病数据平台的构建与应用[J].中医杂志,2026,67(07):770-775. DOI： 10.13288/j.11-2166/r.2026.07.012.

ZHU Yuxin,ZHAO Liping,LU Jiafa,et al.Construction and Application of a Multicenter Traditional Chinese Medicine Proctology Disease Data Platform Based on Multimodal Large Models[J].Journal of Traditional Chinese Medicine,2026,67(07):770-775. DOI： 10.13288/j.11-2166/r.2026.07.012.

摘要

构建基于多模态大模型的混合痔中医专病数据集平台并对其进行初步应用验证。平台采用StarRocks建立四级数据仓库体系，实现多源异构数据的汇聚、清洗与标准化；以DeepSeek-R1-Distill-Qwen-7B大模型为基座，通过低秩自适应（LoRA）技术进行领域微调，结合LLaMA-3.3自然语言处理与思维链技术，实现对非结构化中医病历的智能解析与结构化提取，准确识别症状、证候等6大类、28子类实体，微调后模型F1值达93.8%。平台建立了包含超5万份病历的高质量专病数据集，并已应用于一项涉及17 831例患者的真实世界研究，初步验证了中医传承手术的疗效。

Abstract

This paper has constructed a traditional Chinese medicine （TCM） specialized disease dataset platform for mixed hemorrhoids based on a multimodal large model， and the preliminary application has been validated. The platform uses StarRocks to establish a four-level data warehouse system， enabling the aggregation， cleaning， and standardization of multi-source heterogeneous data. Using DeepSeek-R1-Distill-Qwen-7B as the base model， domain fine-tuning is performed through low-rank adaptation （LoRA） technology. Combined with LLaMA-3.3 natural language processing and reasoning chain techniques， the platform enables intelligent parsing and structured extraction of unstructured TCM medical records. It accurately identifies six major categories and 28 subcategories of entities， including symptoms and syndromes， with a fine-tuned model F1 score of 93.8%. The platform has established a high-quality specialized disease dataset containing more than 50

000 medical records and has been applied in a real-world study involving 17

831 patients， preliminarily verifying the efficacy of TCM heritage surgery.

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Keywords

references

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Center for Evidence-Based Medicine，Beijing University of Chinese Medicine

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