A Novel Approach for Identifying Relevant Genes for Breast Cancer Survivability on Specific Therapies.

ABSTRACT: Analyzing the genetic activity of breast cancer survival for a specific type of therapy provides a better understanding of the body response to the treatment and helps select the best course of action and while leading to the design of drugs based on gene activity. In this work, we use supervised and nonsupervised machine learning methods to deal with a multiclass classification problem in which we label the samples based on the combination of the 5-year survivability and treatment; we focus on hormone therapy, radiotherapy, and surgery. The proposed nonsupervised hierarchical models are created to find the highest separability between combinations of the classes. The supervised model consists of a combination of feature selection techniques and efficient classifiers used to find a potenti

SUBMITTER: Tabl AA 

PROVIDER: S-EPMC6088467 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature