title: Determination of compound aminopyrine phenacetin tablets by using artificial neural networks combined with principal components analysis.
abstract: A method for simultaneous, nondestructive analysis of aminopyrine and phenacetin in compound aminopyrine phenacetin tablets with different concentrations has been developed by principal component artificial neural networks (PC-ANNs) on near-infrared (NIR) spectroscopy. In PC-ANN models, the spectral data were initially analyzed by principal component analysis. Then the scores of the principal components were chosen as input nodes for the input layer instead of the spectral data. The artificial neural network models using the spectral data as input nodes were also established and compared with the PC-ANN models. Four different preprocessing methods (first-derivative, second-derivative, standard normal variate (SNV), and multiplicative scatter correction) were applied to three sets of NIR spectra of compound aminopyrine phenacetin tablets. The PC-ANNs approach with SNV preprocessing spectra was found to provide the best results. The degree of approximation was performed as the selective criterion of the optimum network parameters.
authors.affiliation: Department of Analytical Chemistry, College of Chemistry, Jilin University, Changchun 130021, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Dou
authors.forename: Hong
authors.initials: H
authors.lastname: Mi
authors.forename: Lingzhi
authors.initials: L
authors.lastname: Zhao
authors.forename: Yuqiu
authors.initials: Y
authors.lastname: Ren
authors.forename: Yulin
authors.initials: Y
authors.lastname: Ren
mesh_terms: D000632:Aminopyrine / Q000032:analysis*; D004338:Drug Combinations; D016571:Neural Networks, Computer; D010615:Phenacetin / Q000032:analysis*; D025341:Principal Component Analysis / Q000379:methods; D013055:Spectrophotometry, Infrared; D013607:Tablets / Q000032:analysis
chemical_list: D004338:Drug Combinations; D013607:Tablets; D000632:Aminopyrine; D010615:Phenacetin