Statistical analysis method and system for clinical research of traditional Chinese medicine based on syndrome pattern logic network

By constructing a TCM syndrome logic network, the entire process of TCM clinical research is structured and causal modeled, solving the problems of low data processing efficiency and poor result reliability in TCM research, and improving the scientific nature and operational efficiency of the research.

CN121011313BActive Publication Date: 2026-06-09BEIJING XIAOTANGSHAN HOSPITAL (BEIJING XIAOTANGSHAN SANATORIUM BEIJING XIAOTANGSHAN REHABILITATION HOSPITAL BEIJING INT MEDICINAL FOOD MUSEUM BEIJING HEALTH MANAGEMENT PROMOTION CENT)
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIJING XIAOTANGSHAN HOSPITAL (BEIJING XIAOTANGSHAN SANATORIUM BEIJING XIAOTANGSHAN REHABILITATION HOSPITAL BEIJING INT MEDICINAL FOOD MUSEUM BEIJING HEALTH MANAGEMENT PROMOTION CENT)
Filing Date
2025-08-11
Publication Date
2026-06-09

AI Technical Summary

Technical Problem

The lack of modeling mechanisms for TCM characteristic variables in TCM clinical research, coupled with the poor adaptability of general statistical tools, leads to low data processing efficiency, poor result reliability, high research operation threshold, and difficulty in efficient application in multi-center, large-scale studies.

Method used

We construct a TCM syndrome logic network that integrates causal inference and knowledge graphs. Through data structuring, causal modeling, variable screening, and bias control, we achieve automated and standardized analysis of the entire TCM clinical research process.

Benefits of technology

The systematic processing of multimodal TCM data improves the scientific rigor and data processing efficiency of TCM clinical research, standardizes causal inference capabilities and result interpretation, and provides a scalable analytical framework.

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Abstract

The present application provides a statistical analysis method and system for traditional Chinese medicine clinical research based on syndrome logic network, and relates to the technical field of traditional Chinese medicine informatization and medical statistical analysis. The present application covers the structured processing of traditional Chinese medicine clinical multi-modal raw data, the construction of label set, the research design and the identification of covariates, constructs a structured logic network combining a causal inference model and a traditional Chinese medicine knowledge graph, adopts statistical and machine learning methods for key variable screening and multi-task modeling, completes bias correction and difference significance test under the grouping strategy, and outputs a standardized research report based on traditional Chinese medicine terminology, significantly improves the level of traditional Chinese medicine clinical research in data processing automation, causal analysis accuracy and result clinical interpretability, and provides a systematic analysis framework and technical support for evidence-based research and intelligent auxiliary decision-making of traditional Chinese medicine.
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