Comparison of neural network and multiple linear regression as dissolution predictors

Drug Development and Industrial Pharmacy

Volumn 29, Issue 3, 2003, Pages 349-355

  Sathe, Pradeep M ^a   Venitz, Jurgen ^b  

^a CENTER FOR DRUG EVALUATION AND RESEARCH   (United States)

^b VIRGINIA COMMONWEALTH UNIVERSITY   (United States)

Author keywords

Dissolution; Multiple linear regression; Neural network; Prediction

Indexed keywords

DILTIAZEM; ETHYL CELLULOSE; EUDRAGIT; HYDROXYPROPYLCELLULOSE; HYDROXYPROPYLMETHYLCELLULOSE; MICROCRYSTALLINE CELLULOSE;

ACCURACY; ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; DRUG COATING; DRUG SOLUBILITY; IN VITRO STUDY; INTERMETHOD COMPARISON; LINEAR REGRESSION ANALYSIS; PREDICTION; TABLET FORMULATION;

CHEMISTRY, PHARMACEUTICAL; DILTIAZEM; LINEAR MODELS; MULTIVARIATE ANALYSIS; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS; SOLUBILITY; TABLETS;

EID: 0038302764     PISSN: 03639045     EISSN: None     Source Type: Journal    
DOI: 10.1081/DDC-120018209     Document Type: Article

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