Two modelling data analytical methods applied to optimise the preparation of norcantharidin chitosan nanoparticles

Journal of Experimental Nanoscience

Volumn 5, Issue 3, 2010, Pages 271-284

  Zhang, Wei ^a   Liu, Yang ^a   Chen, Xiao Yan ^a   Bei, Yong Yan ^a   Xu, Jing Yu ^a   Wang, Wen Juan ^a   Zhang, Xue Nong ^a   Zhang, Qiang ^b  

^a SOOCHOW UNIVERSITY   (China)

^b PEKING UNIVERSITY HEALTH SCIENCE CENTER   (China)

Author keywords

Artificial neural networks; Chitosan; Nanoparticles; Non linear regression

Indexed keywords

ANALYTICAL METHOD; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; BACKPROPAGATION NETWORK; CHITOSAN NANOPARTICLES; CROSS-LINKAGE; DRUG VEHICLES; ENTRAPMENT EFFICIENCY; LOW MOLECULAR WEIGHT; MULTIPLE REGRESSION MODEL; NON-LINEAR REGRESSION; OPTIMAL CONDITIONS; OPTIMAL RESULTS; PREPARATION CONDITIONS; SODIUM TRIPOLYPHOSPHATE; WEIGHTED SUM;

BACKPROPAGATION; CHITIN; CHITOSAN; DATA FLOW ANALYSIS; LINEAR REGRESSION; NANOPARTICLES; OPTIMIZATION; PARTICLE SIZE; SODIUM;

NEURAL NETWORKS;

CHITOSAN; DRUG VEHICLE; NANOPARTICLE; NORCANTHARIDIN; POLOXAMER; TRIPOLYPHOSPHATE;

ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHINESE MEDICINE; CROSS LINKING; MOLECULAR WEIGHT; NANOTECHNOLOGY; NONLINEAR REGRESSION ANALYSIS; PARTICLE SIZE; PRIORITY JOURNAL; SYNTHESIS; TEMPERATURE;

EID: 77954287550     PISSN: 17458080     EISSN: 17458099     Source Type: Journal    
DOI: 10.1080/17458080903513284     Document Type: Article

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