Breast Cancer Prognosis and Prediction through Gene Expression Analysis and the Hybrid Model of SVM and Logistic Regression
Shalini Puri, Manish Kant Dubey, Shirish Mohan Dubey · 2023
Breast cancer is one of the most challenging issues in the health industry today. It takes many lives per year around the globe. It must be diagnosed at the early stages so that it can be cured timely. Several hypotheses and research works have been proposed to date, however many of them do not handle large data sets, and some of them do not provide promising results. On the other side, gene expression analysis for breast cancer prediction is a rapidly evolving field with great potential for future advancements. This paper proposes a novel approach for breast cancer detection using gene expression analysis. It implements machine learning techniques such as SVM and logistic regression to detect methylated DNA and breast cancer classification, respectively. It predicts whether the patient with methylated DNA has breast cancer or not, and it achieved an accuracy of 94.73%.