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Title

Breast Cancer Images Classification using Convolution Neural Network

Author

Mohammed Yahya Alzahrani

Citation

Vol. 23  No. 8  pp. 113-120

Abstract

One of the most prevalent disease among women that leads to death is breast cancer. It can be diagnosed by classifying tumors. There are two different types of tumors i.e: malignant and benign tumors. Physicians need a reliable diagnosis procedure to distinguish between these tumors. However, generally it is very difficult to distinguish tumors even by the experts. Thus, automation of diagnostic system is needed for diagnosing tumors. This paper attempts to improve the accuracy of breast cancer detection by utilizing deep learning convolutional neural network (CNN). Experiments are conducted using Wisconsin Diagnostic Breast Cancer (WDBC) dataset. Compared to existing techniques, the used of CNN shows a better result and achieves 99.66%% in term of accuracy.

Keywords

Breast cancer, deep learning, convolutional neural network, feature selection, WDBC dataset.

URL

http://paper.ijcsns.org/07_book/202308/20230815.pdf