Breast Cancer Diagnosis with Machine Learning

Abstract

An early-stage breast cancer diagnosis usually results in a high survival rate within five years. This research seeks the feasibility of applying a specific machine learning algorithm, logistic regression, to a public dataset. The result is two models, reaching accuracies of 0.965 and 0.936. It confirms that the generality of applying machine learning algorithms is beneficial to medical diagnosis. Even though this is not the first research to exploit the application of machine learning in the medical field, it still provides some valuable insights for future research.