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[Qualitative recognition on omitted ingredients in Liuwei Dihuang Pills by Bayesian analysis and PRIMA]
Abstract
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.
Result:
The classification average accuracy was 100% for four patterns by Bayesian analysis, and 99.6% by PRIMA analysis.
Conclusion:
Bayesian analysis and PRIMA analysis can be used to classify and recognize the omitted ingredients in Liuwei Dihuang Pills.