Study on classification of the efficacy of traditional Chinese medicine based on FAAS combined with chemometrics methods

Author

Gao, Jinhong ; Tian, Xinling ; Li, Jifeng

Author_Institution

Dept. of Chem. & Chem. Eng., Weinan Teachers Coll., Weinan, China

fYear

2011

fDate

24-26 June 2011

Firstpage

7879

Lastpage

7882

Abstract

This paper applies flame atomic absorption spectrophotometry to determine the content of metallic element in 24 kinds of TMC. Chemo-metric approaches, including Hierarchical Clustering Analysis (HCA), Principal Component Analysis (PCA), and Probabilistic Neural Network (PNN) are used to carry out classified analysis on TCM efficacy, and the results show that this research on TCM efficacy using the approach combined FAAS with chemometrics has a scientific reference value for the further TCM efficacy analysis.

Keywords

chemistry computing; data analysis; drugs; medical computing; neural nets; pattern clustering; principal component analysis; probability; spectrochemical analysis; FAAS; TCM efficacy classification; chemometrics; flame atomic absorption spectrophotometry; hierarchical clustering analysis; metallic element content determination; principal component analysis; probabilistic neural network; traditional Chinese medicine; Artificial neural networks; Blood; Chemical elements; Chemicals; FAA; Principal component analysis; Probabilistic logic; Classification; chemometrics; traditional Chinese medicine (TCM);

fLanguage

English

Publisher

ieee

Conference_Titel

Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-9172-8

Type

conf

DOI

10.1109/RSETE.2011.5966265

Filename

5966265