Volume 01,Issue 04

Breast Cancer Diagnosis Using Fuzzy Feature and Optimized Neural Network via the Gbest-Guided Artificial Bee Colony Algorithm

Authors

Massoud Pourmandi, Jalil Addeh

Abstract
The correct diagnosis of the breast cancer is one of the major problems in the medical field. This paper presents an improved classifier for automated diagnostic systems of breast cancer tumors. The proposed diagnostic system consists of a combined fuzzy clustering optimized neural network (FCONN) algorithm for the classification of the breast cancer tumors using fuzzy c-means clustering (FCM) algorithm and optimized neural network. FCM is used for extracting the efficient features and ONN is used for intelligent classification. In neural networks training, the hyper-parameters have very important roles for their recognition accuracy. Therefore, Gbest-guided artificial bee colony (GABC) algorithm is proposed for selecting the appropriate parameters of the classifier. The proposed system is tested on Wisconsin Breast Cancer (WBC) database and simulation results show that the recommended system has a high accuracy.

Keyword: Breast cancer, Fuzzy clustering, Gbest-guided artificial bee colony, Neural network, Optimization.

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