Pattern recognition and its application in quality assessment of Chinese materia medica
10.7501/j.issn.0253-2670.2016.23.027
- Author:
Lu-Lu WANG
1
Author Information
1. College of Medicine, Changchun University of Science and Technology
- Publication Type:Journal Article
- Keywords:
Artificial neural networks;
Chinese materia medicine;
Pattern recognition;
Principal component analysis;
Quality assessment
- From:
Chinese Traditional and Herbal Drugs
2016;47(23):4282-4288
- CountryChina
- Language:Chinese
-
Abstract:
In recent years, with the development of Chinese materia medica (CMM) industry, the problem of quality control method is not comprehensive. It becomes the most important factor to block the development of CMM. Many scholars look for some new methods, by which the quality of CMM could be assessed objectively and accurately. Since 1980s, the pattern recognition was introduced to the chemical field and was applied to CMM at the same time. And there were some CMM quality assessment methods based on the pattern recognition established so far. In this article, the latest research progress in the pattern recognition, basic principle, and technology, was introduced and the applications in principal component analysis, cluster analysis, discriminant analysis, grey correlation analysis, partial least squares, heuristic evolving latent projections and artificial neural networks of CMM quality assessment have been reviewed, so as to provide the reference for further studies and application in CMM.
