WASET
	@article{(Open Science Index):https://publications.waset.org/pdf/12668,
	  title     = {Diagnosis of Ovarian Cancer with Proteomic Patterns in Serum using Independent Component Analysis and Neural Networks},
	  author    = {Simone C. F. Neves and  LĂșcio F. A. Campos and  Ewaldo Santana and  Ginalber L. O. Serra and  Allan K. Barros},
	  country	= {},
	  institution	= {},
	  abstract     = {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.},
	    journal   = {International Journal of Biomedical and Biological Engineering},
	  volume    = {4},
	  number    = {12},
	  year      = {2010},
	  pages     = {562 - 565},
	  ee        = {https://publications.waset.org/pdf/12668},
	  url   	= {https://publications.waset.org/vol/48},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 48, 2010},
	}