An Expanded Vision of Breast Cancer Diagnosis Approaches Based on Machine Learning Techniques

Breast cancer is one of the leading causes of death among women all over the world, it is happened due to the uncontrollable growth of breast cells. The only rescue to reduce a breast cancer fatality is the early detection and appropriate diagnosis. In medical fields, the accurate classification of tumors is a very important task. Machine Learning techniques are widely employed in detecting and classifying different types of cancers because of their high performance and accurate results. In this paper, an overall expansion of breast cancer diagnosis based on different machine learning techniques is presented. Many techniques have been developed, techniques based on Artificial Neural Network (ANN), techniques based on Support Vector Machine (SVM) and techniques based on Relevance Vector Machine for diagnosing of breast cancer.