Survival Analysis of Breast Cancer using Machine Learning
Harish Sanmugam J, Adithya Menon S, Harivarsha Ellanghovan · 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC) · 2022
Cancer is a particularly varied ailment that results from pursuing allure, progress, and asperity, which is amazingly troublesome. The most ordinary malignancy-producing structure is the TNM (carcinoma, growth, often major) arrangement that is located generally on dispassionate news like swelling intensity, consideration of spread, etc. Combining phenotypic and microscopic dossiers from tumor victims can result in more specific writings of disease progression and asperity. investigated the accompanying three microscopic datasets (DNA methylation, RNASeq and miRNASeq dossiers) in addition to the clinical dataset to conclude the overall endurance of feeling malignancy sufferers. The machine intelligence algorithms conclude the maximal accuracy of the survival rates.