An Efficient Cluster Based Deep Neural Network (C-DNN) for Detection of Heart Disease

Abstract

The term ‘heart disease’ refers to circumstances that block blood vessels and may lead to a heart attack, chest pain or stroke. The heart conditions will the affect heart’s muscle, valves or rhythm leading to heart diseases and bypass surgery or coronary intervention is used for solving these issues. In this research work, an effective Cluster based Deep Neural Network approach is proposed to detect the angiographic heart disease (i.e. to detect the patients with  50% diameter reduction of a major coronary artery). The data set is grouped using K-Means clustering algorithm and then the heart disease is predicted using cluster based deep learning approach. The proposed method is compared with various parameters for classifier algorithms like DNN, SVM- Linear, SVM- polynomial, KNN, ELM, ELM- cluster and the model is better in this work.

Keywords: Deep Neural Network; Heart Disease; cluster