Diagnosis of Ovarian Cancer with Proteomic Patterns in Serum using Independent Component Analysis and Neural Networks

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.

Authors:

• Simone C. F. Neves
• Lúcio F. A. Campos
• Ewaldo Santana
• Ginalber L. O. Serra
• Allan K. Barros

Keywords:

• Cancer ovarian
• Proteomic patterns in serum
• independent component analysis and neural networks.

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