%0 Journal Article
	%A M. Sinecen and  M. Makinac─▒
	%D 2007
	%J International Journal of Medical and Health Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 7, 2007
	%T Classification of Prostate Cell Nuclei using Artificial Neural Network Methods
	%U https://publications.waset.org/pdf/14915
	%V 7
	%X The purpose of this paper is to assess the value of neural networks for classification of cancer and noncancer prostate cells. Gauss Markov Random Fields, Fourier entropy and wavelet average deviation features are calculated from 80 noncancer and 80 cancer prostate cell nuclei. For classification, artificial neural network techniques which are multilayer perceptron, radial basis function and learning vector quantization are used. Two methods are utilized for multilayer perceptron. First method has single hidden layer and between 3-15 nodes, second method has two hidden layer and each layer has between 3-15 nodes. Overall classification rate of 86.88% is achieved.

	%P 474 - 476