Study on TCM Syndrome Identification Modes of Coronary Heart Disease Based on Data Mining
Qi Shi1, Huihui Zhao, Jianxin Chen
1Beijing University of Chinese Medicine, 11 Bei San Huan Dong Lu, ChaoYang District, Beijing 100029, China.
Insights
Traditional Chinese Medicine (TCM) offers treatments for coronary heart disease (CHD). This study uses complex network and CHAID decision tree methods to identify TCM core syndromes in CHD patients based on biological data.
Area of Science:
- Integrative medicine
- Systems biology
- Cardiology
Background:
- Coronary heart disease (CHD) presents high incidence and mortality.
- Traditional Chinese Medicine (TCM) is vital for CHD treatment.
- Traditional diagnostic methods face challenges with systems biology advancements.
Purpose of the Study:
- To identify TCM core syndromes in CHD patients.
- To establish TCM syndrome identification models using biological parameters.
- To validate these models using external data.
Main Methods:
- Complex network analysis.
- CHAID decision tree algorithm.
- Biological parameter integration.
Main Results:
- Identification of TCM core syndromes for CHD.
- Development of TCM syndrome identification models.
- Successful external validation of the models.
Conclusions:
- Complex network and CHAID methods effectively identify TCM syndromes in CHD.
- Biological parameters can be integrated into TCM syndrome identification.
- Validated models offer a new approach for TCM in CHD.
Abstract:
Coronary heart disease (CHD) is one of the most important types of heart disease because of its high incidence and high mortality. TCM has played an important role in the treatment of CHD. Syndrome differentiation based on information from traditional four diagnostic methods has met challenges and questions with the rapid development and wide application of system biology. In this paper, methods of complex network and CHAID decision tree were applied to identify the TCM core syndromes of patients with CHD, and to establish TCM syndrome identification modes of CHD based on biological parameters. At the same time, external validation modes were also constructed to confirm the identification modes.
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