Artificial neural network as an alternative to multiple regression analysis in optimizing formulation parameters of cytarabine liposomes

AAPS PharmSciTech

Volumn 5, Issue 1, 2004, Pages

  Subramanian, Narayanaswamy ^a   Yajnik, Archit ^a   Murthy, Rayasa S Ramachandra ^a  

^a M S UNIVERSITY OF BARODA   (India)

Author keywords

Artificial neural network; Contour plots; Cytarabine liposomes; Factorial design; Multiple regression

Indexed keywords

CHOLESTEROL; CYTARABINE; LIPOSOME; PHOSPHATIDYLCHOLINE;

ACCURACY; ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER SYSTEM; CONTROLLED STUDY; DRUG FORMULATION; MULTIPLE REGRESSION; PREDICTION; PROCESS OPTIMIZATION; STUDENT T TEST; ARTIFICIAL INTELLIGENCE; CHEMISTRY; COMPARATIVE STUDY; REGRESSION ANALYSIS;

ARTIFICIAL INTELLIGENCE; CHEMISTRY, PHARMACEUTICAL; CYTARABINE; LIPOSOMES; NEURAL NETWORKS (COMPUTER); REGRESSION ANALYSIS;

EID: 23144462228     PISSN: 15309932     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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