Support vector machines versus artificial neural network: Who is the winner? [4]

Kidney International

Volumn 71, Issue 1, 2007, Pages 84-

  Tonello, L ^a   Vescini, F ^a   Caudarella, R ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTIFICIAL NEURAL NETWORK; COMPARATIVE STUDY; DATA BASE; INFORMATION PROCESSING; LETTER; PRIORITY JOURNAL; STATISTICAL ANALYSIS; SUPPORT VECTOR MACHINE; URETER STONE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; LOGISTIC MODELS; NEURAL NETWORKS (COMPUTER); URETERAL CALCULI;

EID: 33845689260     PISSN: 00852538     EISSN: 15231755     Source Type: Journal    
DOI: 10.1038/sj.ki.5001907     Document Type: Letter

References (3)

1. Dal Moro F, Abate A, Lanckriet GRG et al. A novel approach for accurate prediction of spontaneous passage of ureteral stones: support vector machines. Kidney Int 2006; 69: 157-160.
2. McClelland JL, Rumelhart DE. Exploration in Parallel Distributed Processing. The MIT Press: Cambridge, 1998.
3. Master T. Practical Neural Network Recipes in C++. Academic Press: New York, 1993.