Breast Cancer Diagnosis Using Machine Learning Techniques

Cancer is one of the malignant diseases and millions of people worldwide die from cancer annually. Breast cancer diagnosis requires the analysis of images and attributes as well as collecting many clinical and mammography variables. In diagnosis of breast cancer, it is important to determine whether a tumor is benign or malignant. The information about breast cancer risk prediction along with the type of tumor are crucial for patients and effective medical decision making. An ideal diagnostic system could effectively distinguish between benign and malignant cells; however, such a system has not been created yet. In this study, a model is developed to improve the prediction probability of breast cancer. It is necessary to have such a prediction model as the survival probability of breast cancer is high when patients are diagnosed at early stages.