%0 Journal Article
	%A Simone C. F. Neves and  Lúcio F. A. Campos and  Ewaldo Santana and  Ginalber L. O. Serra and  Allan K. Barros
	%D 2010
	%J International Journal of Biomedical and Biological Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 48, 2010
	%T Diagnosis of Ovarian Cancer with Proteomic Patterns in Serum using Independent Component Analysis and Neural Networks
	%U https://publications.waset.org/pdf/12668
	%V 48
	%X We propose a method for discrimination and
classification of ovarian with benign, malignant and normal tissue
using independent component analysis and neural networks. The
method was tested for a proteomic patters set from A database, and
radial basis functions neural networks. The best performance was
obtained with probabilistic neural networks, resulting I 99% success
rate, with 98% of specificity e 100% of sensitivity.
	%P 562 - 565