Prediction of cardiovascular disease using deep learning algorithms to prevent COVID 19

Abstract

ABSTRACT The leading cause of mortality is due to cardio vascular disease (CVD) globally. CVD is the major cause of death all over the world for the past years because an estimation of 17.5 million people died from CVD in 2012 and premature death from CVD is 37% below the age of 70. In health-care field, the data generated are large, critical, and more complex and multi-dimensional. In the current situation, the medical professionals working in the field of heart disease can predict up to 67% accuracy but the doctors need an accurate prediction of heart disease. The ultimate goal of this study is to early prediction of CVD by enhancing both predictive analysis and probabilistic classification. Deep learning techniques such as CNN and RNN emulate human cognition and learn from training examples to predict future events. As a result, the future prediction of the cardiovascular disease has been found. The prediction of CVD can be used for the prevention of COVID-19 disease using deep learning algorithm. So, this can be employed to detect the early stage of the disease. The importance of the CVD refers to the conditions like narrowed or blocked blood vessels which may lead to some other diseases like heart attack, chest pain or stroke.