@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}, }