An Integrative Machine Learning Framework For Classifying Seer Breast Cancer

This article discusses the use of Artificial Intelligence and Machine Learning in the diagnosis and prediction of breast cancer. It reviews various methods such as correlation analysis, Principal Component Analysis (PCA), Supervised and Unsupervised learning, Crystall algorithm, Minimal Redundancy Maximal Relevance and Chi-Square Algorithms, and Deep Learning. It also outlines the goal of the research which is to classify and predict the alive and death status of cancer patients.