Early Detection of Breast Cancer Through Supervised Machine Learning

An effective way to reduce the high mortality rate of breast cancer is to detect it at an early stage. Prevention is still a mystery and the only way to reduce the mortality rate of patients by early detection. One of the primary goals of machine learning is to device an efficient algorithm for training computers to automatically acquire effective and accurate model from experience. It is providing a technique, method tools that can assist in solving prognosis and diagnosis problems in a variety of medical domains. It is argued that the successful implementation of ML methods can help the integration of computer-based systems in the healthcare environment providing opportunities to facilitate and enhance the work of medical experts and ultimately to improve the efficiency and quality of medical care. Classification techniques are reducing the possible errors that might be made because of unverified experts; provide more detailed medical data for examination in a shorter time.