Study on syndrome quantification, differentiation and classification of traditional Chinese medicine with data envelopment analysis.
- Author:
Qing-Bo MENG
1
;
Yi-Xin YIN
;
De-Zheng ZHANG
;
Guo-Ping YANG
Author Information
1. School of Automation, University of Science and Technology, Beijing 100083, China.
- Publication Type:Journal Article
- MeSH:
Data Mining;
Diagnosis, Differential;
Drugs, Chinese Herbal;
therapeutic use;
Humans;
Medicine, Chinese Traditional;
Models, Theoretical;
Phytotherapy
- From:
China Journal of Chinese Materia Medica
2013;38(10):1631-1642
- CountryChina
- Language:Chinese
-
Abstract:
To raise the syndrome sequence quantification, differentiation and classification algorithm based on data envelopment analysis for solving the modeling issue of syndrome differentiation and classification of traditional Chinese medicine (TCM). This algorithm has three steps: first, in order to obtain basic units for explaining pathogenesis, and establish a syndrome collection on this basis mechanisms of syndrome differentiation and classification were analyzed and classified according to TCM theory, mechanisms of syndrome differentiation and classification were analyzed and classified according to TCM theory; second, regularity and syndromes of corresponding prescriptions were sought according to the incidence and development progress of syndromes, and mathematical tools of data envelopment analysis were used to calculate state data of syndromes in each stage and obtain quantitative syndrome sequence; finally, syndrome sequence was taken as the measurement standard to quantify candidate syndromes and diagnostic information, and the similarity was calculated to obtain the matching degree between diagnostic information and candidate syndromes, so as to complete the syndrome differentiation and classification calculation. According to the results of model-based reasoning, the algorithm could indicate the regularity implied in prescription materials, and grasp the dynamic process of syndromes in an all-round way, and its results were verified through calculation and analysis on clinical cases. At least, it provides an idea for quantitative modeling of TCM.
