Evaluation of chemometric techniques and artificial neural networks for cancer screening using Cu, Fe, Se and Zn concentrations in blood serum

Analytica Chimica Acta

Volumn 533, Issue 2, 2005, Pages 161-168

  Hernández Caraballo, Edwin A ^a,b   Rivas, Francklin ^b   Pérez, Anna G ^b   Marcó Parra, Lué M ^b  

^a UNIVERSIDAD CENTROCCIDENTAL LISANDRO ALVARADO   (Venezuela)

^b UNIVERSIDAD DE LOS ANDES   (Venezuela)

Author keywords

Artificial neural networks (ANNs); Backpropagation neural network (BpNN); Cancer; Copper; Iron; Logistic regression; Principal components analysis (PCA); Probabilistic neural network (PrNN); Selenium; Serum; Zinc

Indexed keywords

COPPER; FLUORESCENCE; IRON; PRINCIPAL COMPONENT ANALYSIS; SCREENING; SELENIUM; TUMORS; X RAY SPECTROSCOPY; ZINC;

ARTIFICIAL NEURAL NETWORKS (ANN); BACKPROPAGATION NEURAL NETWORK (BPNN); LOGISTIC REGRESSION; PROBABILISTIC NEURAL NETWORK (PRNN); SERUM;

NEURAL NETWORKS;

COPPER; IRON; SELENIUM; ZINC;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER; CANCER SCREENING; CHEMOMETRIC ANALYSIS; CONTROLLED STUDY; COPPER BLOOD LEVEL; DIAGNOSTIC VALUE; HUMAN; INTERMETHOD COMPARISON; IRON BLOOD LEVEL; LOGISTIC REGRESSION ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SELENIUM BLOOD LEVEL; TRACE METAL BLOOD LEVEL; X RAY FLUORESCENCE; ZINC BLOOD LEVEL;

EID: 25444529966     PISSN: 00032670     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aca.2004.10.087     Document Type: Article

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