Predicting breast cancer risk using subset of genes

© 2019 IEEE. An accurate prediction of breast cancer risk can enable physicians to detect the cancer at an early stage. This paper is focused on the problem of predicting breast cancer risk based on a subset of genes. We developed a breast cancer risk prediction model based on an ensemble of Deep Neural Network (DNN) and Support Vector Machine (SVM) approaches. The proposed model was evaluated based on microarray gene expression dataset using accuracy, precision, and recall matrices and compared it with existing work. The outcomes of the experiment show that the proposed approach can predict breast cancer much more accurately based on genes as compared to the existing models.