Science & Technology Review >

2024 , Vol. 42 >Issue 21: 149 - 162

DOI: https://doi.org/10.3981/j.issn.1000-7857.2024.05.00473

Exclusive: The paradigm and application of clinical research in traditional Chinese medicine

The study on the formula characteristics of Zhengan Xifeng decoction in the treatment of hypertension based on machine learning models

  • HUAN Jiaming ,
  • CHEN Xiaoqing ,
  • YANG Wenqing ,
  • LI Jie ,
  • HUA Zhen ,
  • WANG Yifei ,
  • LI Yunlun
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  • 1. First School of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, China;
    2. Department of Cardiovascular, Hospital of East Gaoxin District of Jinan, Jinan 250101, China;
    3. Innovation Research Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, China;
    4. Department of Cardiovascular, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, China;
    5. Precision Diagnosis and Treatment of Cardiovascular Diseases with Traditional Chinese Medicine Shandong Engineering Research Center, Jinan 250355, China

Received date: 2023-11-02

  Revised date: 2024-08-30

  Online published: 2024-12-14

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Abstract

The high prevalence of hypertension and its wide range of complications have made it a significant risk factor for cardiovascular disease mortality.Zhengan xifeng decoction (ZXD) is a classic traditional Chinese medicine prescription used in the clinical treatment of hypertension.However, there is a lack of systematic analysis of its composition rules and biological effects.In order to further explore the clinical application characteristics of ZXD in the treatment of hypertension, this study established a dataset based on the electronic medical records of hypertension patients from the Affiliated Hospital of Shandong University of Traditional Chinese Medicine from 2011 to 2019.Apriori algorithm was used to quantify the compatibility strength of the Chinese medicines in ZXD, while convolutional neural networks were employed to quantify the dosage characteristics.Topological feature analysis of protein interactions was used to examine biological characteristics.The outcome was then input into k-nearest neighbors, support vector machines, gradient boosting decision trees, Bayesian networks, and logistic regression models to evaluate the efficacy of each model, reflecting the composition rules and mechanisms of action of ZXD from multiple dimensions.The results showed that the k-nearest neighbors algorithm performed the best among the five models (AUC=93.5%), identifying 87 effective combinations, validating the mechanisms by which ZXD regulates cytokines, reduces inflammation, and corrects metabolic disorders.External testing indicated that this research could be extrapolated to other diseases.This study demonstrates that the model effectively integrates convolutional neural network data and network topology data, incorporating dosage information and biological characteristics into the exploration of Chinese medicine combinations.It complements traditional association rule models and has good general applicability and extrapolation capability, providing an interdisciplinary research approach for mining multimodal Chinese medicine datasets.

Key words： machine learning; real world data; data mining; zhengan xifeng decoction; hypertension

Cite this article

HUAN Jiaming , CHEN Xiaoqing , YANG Wenqing , LI Jie , HUA Zhen , WANG Yifei , LI Yunlun . The study on the formula characteristics of Zhengan Xifeng decoction in the treatment of hypertension based on machine learning models[J]. Science & Technology Review, 2024 , 42(21) : 149 -162 . DOI: 10.3981/j.issn.1000-7857.2024.05.00473

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