Prediction of Risk Level and Survivability of Breast Cancer Patients Using Machine Learning Techniques

Breast cancer is the preeminent cancer among women and the second main cause of mortality of cancer. Early detection of breast cancer and prediction of survivability after the cancer is the most consequential medicine area. In the present, for predicting and anticipating future survivability of breast cancer, several researches had been conducted and developed algorithms for breast cancer prediction and there are many treatment methods for breast cancer patients to determine the patient's ability to live and inability to survive. In this context, a proper risk prediction system was developed in Sri Lanka context for the general community who with or without a diagnosis of breast cancer could not be identified. Furthermore, for the patients who are diagnosed, there is no and no hierarchical system to predict the relationship between the survivals of patients. The aim of this study is to utilize risk variables to create a prediction model that is an adequate method for predicting the present risk level of a person and for the diagnosis of patients for the prediction of survivability of patients using the treatment of breast cancer. The proposed machine learning models are expected for integrating computer-aided diagnosis systems for detecting breast cancer disease and predicting survivability.