Deep learning network for identification of ischemia using clinical data

Abstract

Ischemic heart disease is amongst the foremost reasons of death and disability majorly because of atherosclerosis and other cardiovascular syndromes like cerebrovascular accidents and myocardial infarction. Ischemia can be diagnosed by using invasive & non-invasive methods. Invasive methods are generally expensive and always requires high level of technical and medical expertise. This paper focuses on a bio inspired optimization approach for the identification of effective biomarkers and deep learning based neural network technique on non-invasive clinical parameters to diagnose Ischemia with more accuracy. For experiment purpose, the clinical data of Coronary Artery disease (CAD) patients was collected from the cardiology department of Medical College, Shimla, India. The proposed method improves the prediction accuracy of Ischemia.