Data Mining-Based Study on the Medication Rules of Renowned Chinese Medicine Practitioners in Treating Back Pain?

Corresponding author: zengjingqi, zengjingqi4317@hnucm.edu.cn

DOI: 10.12201/bmr.202510.00020

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  Abstract: Objective:To analyze the medication rules of Professor Tian Xinyi in treating Back pain based on data mining technology.Methods:A total of 209 outpatient medical records and corresponding prescriptions were collected, involving 84 herbal medicines. The ancient and modern medical case cloud platform (V2.3.5) was used to perform frequency, attribute, channel tropism, association rule, and clustering analyses.Results:High-frequency herbs included Glycyrrhizae Radix (Gancao), Astragali Radix (Huangqi), and Angelicae Sinensis Radix (Danggui), among others. Herbal properties were primarily warm (56.36%) and neutral (28.95%); flavors were mainly sweet (62.31%), pungent (54.87%), and bitter (41.65%). The meridians entered were mostly the Liver (52.68%), Spleen (47.66%), and Kidney (33.22%) meridians. The core efficacies were strengthening bones and tendons, tonifying the liver and kidney, and dispelling wind-damp. Association rule analysis yielded 42 herb pairs, and clustering analysis identified 4 core herb groups.Conclusion:Professor Tian’s treatment of back pain is based on the principle of “supporting healthy qi and eliminating pathogenic factors, addressing both the root and branch,” emphasizing boosting qi and blood, tonifying the liver and kidney, and strengthening bones and tendons to address the root, while dispelling wind-damp and unblocking collaterals to address the branch. The prescription structure is rigorous, reflecting a holistic, multi-target regulatory approach.

  Key words: Back pain; Data mining; Medication rule; Tian Xinyi

  Submit time: 13 October 2025

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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