[Qualitative recognition on omitted ingredients in Liuwei Dihuang Pills by Bayesian analysis and PRIMA].
OBJECTIVE
To qualitatively recognize the omitted ingredients in Liuwei Dihuang Pills by Bayesian analysis and PRIMA.


METHODS
The extracts of the pills were analyzed by HPLC, for each object, the areas of nine peaks relative to that of the internal standard were selected as classification features. The classification model was established on 169 training-set objects.


RESULTS
The classification average accuracy was 100% for four patterns by Bayesian analysis, and 99.6% by PRIMA analysis.


CONCLUSIONS
Bayesian analysis and PRIMA analysis can be used to classify and recognize the omitted ingredients in Liuwei Dihuang Pills.
Zhang
L
L
China Pharmaceutical University, Jiangsu Nanjing 210009, China.
Liu
Z P
ZP
Yang
C
C
D001499:Bayes Theorem; D004338:Drug Combinations; D004340:Drug Contamination; D004365:Drugs, Chinese Herbal / Q000737:chemistry; D010946:Plants, Medicinal
D004338:Drug Combinations; D004365:Drugs, Chinese Herbal; C042579:Liuwei Dihuang Decoction