Intelligent decision support system for breast cancer diagnosis by gene expression profiles

Abstract

Breast cancer transpires as one of the main source of deathly diseases among ladies around the world. Nevertheless, there is confirmation that early recognition and treatment can raise the survival rate of breast cancer patients. This paper presents an Intelligent Decision Support System (IDSS) for breast cancer diagnosis by using gene expression profiles. The proposed system first extracts significant features from the input patterns by utilizing Information Gain (IG) and then employs Deep Genetic Algorithm (DGA) for feature reduction as well as for breast cancer diagnosis. The proposed system is evaluated by considering a benchmark microarray dataset and compared with the most recent systems. The outcomes demonstrate that the proposed IDSS outperforms other systems in terms of diagnosis time and accuracy. The proposed system produces 99.94% classification accuracy. In addition, the proposed system reduces the required memory space.