Application progress of machine learning in study on cold and hot properties of Chinese materia medica
10.3760/cma.j.cn115398-20240119-00230
- VernacularTitle:机器学习在中药寒热药性研究中的应用进展
- Author:
Jiarou WANG
1
;
Lu ZHOU
;
Huimin YUAN
;
Yuhan SHENG
;
Yaqi ZHANG
;
Yang TANG
;
Yan SUN
;
Fengjie ZHENG
;
Yuhang LI
Author Information
1. 北京中医药大学2022级博士研究生，北京 100029
- Keywords:
Four properties (TCD);
Cold and hot properties;
Machine learning;
Review
- From:
International Journal of Traditional Chinese Medicine
2025;47(3):423-428
- CountryChina
- Language:Chinese
-
Abstract:
The scientific interpretation of the theory of medicinal properties of TCM is a research hotspot in the modernization of TCM. It is of great value to clarify the property and degree of cold and heat in Chinese materia medica for guiding clinical precise medication. In recent years, the research on the cold and heat properties of Chinese materia medica has been carried out at the animal, cell and molecular levels. Based on the objective material basis of medicinal properties, from the perspective of biological effects such as thermodynamics and multiomics; with the help of infrared thermal imaging and other technologies for analysis; forming a variety of research models such as "property-structure relationship". Related research has developed from a single material component or index to a new model that tends to integrate multi-source information and multi-dimensional data. However, how to deal with the problems of large sample size, strong redundancy, high heterogeneity, and how to integrate multi-dimensional information are still research difficulties. With its powerful computing and learning ability, machine learning can show good discrimination and prediction ability in the study of cold and hot properties of Chinese materia medica, and play an important role in the study of cold and hot properties of Chinese materia medica. At present, the most widely used algorithms are linear discriminant analysis, Logistic discriminant analysis, support vector machine, decision tree, random forest and so on. The data dimension of the existing research needs to be enriched, the algorithm has room for further optimization, and a more detailed discriminant model of cold and hot properties of Chinese materia medica needs to be established.
