Classification of Breast Cancer using Artificial Neural Network Algorithms

Abstract

Breast cancer is a malignant tumor that has developed from cells of the breast. Breast cancer is one of the most fatal diseases in the world and a relatively common cancer in Turkey. Breast cancer diagnosis has been approached by various machine learning techniques for many years. In this study, two different probabilistic neural network (PNN) structures were used for breast cancer’s diagnosis. The PNN results were compared with the results of the multilayer, learning vector quantization neural networks and the results of the previous reported studies focusing on breast cancer’s diagnosis and using the same dataset. It was observed that the PNN is the best classification accuracy with 98.10% accuracy obtained via 3-fold cross validation. The present paper describes how this technique can be applied to the breast tissue classification and the breast cancer detection for medical devices. The purpose of this study is the classification of the variability of impedivity observed in normal and pathological breast tissue.

Keywords

• breast cancer diagnosis
• artificial neural network
• machine learning based decision support system

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