Breast Cancer Cell Data Analysis and Visualization Using R

Abstract

Breast cancer is the most frequently occurring cancer in women. If the cancer is diagnosed and treated at an early stage, the patient has a survival rate of 99% after 5 years, but it significantly drops to 29% when it reaches a distant stage. Thus, it is very important to detect ‘positive cancer cells’ in the early stage, so I analyzed the 569 breast cancer cell data provided by the University of Wisconsin using R-Studio. Through this program, I visualized the relationships between 10 different cell characteristics, and researched the kind of relationship between radius and positive cancer cells by utilizing graphs. Also, I created a predictive model that can detect positive cancer cells based on logistic regression and training original 569 data. Finally, I recommended the adequate age (35-39) for the breast cancer examination by analyzing the breast cancer statistics. Through this research, I derived effective breast cancer predicting model and deeply explored big data analysis method and data-mining on R-Studio.