Review on Heart Disease Diagnosis Using Deep Learning Methods

Abstract

Developments for automation and advanced computing in the area of medical data processing has outcome with different new learning techniques. Deep learning has evolved as an advanced approach in machine learning applied to different old and new area of applications. Deep learning approaches have evolved as supervised, semi-supervised and un-supervised mode applied for different real time applications. The approach has shown a significant usage for image processing, computer vision, medical diagnosis, robotic and control operation application. Among various usage of machine learning approaches for automation, medical diagnosis has been observed as a new upcoming application. The criticality of data processing, response time, and accuracy in decision, tends the learning system more complex in usage for medical diagnosis. This paper outlines the developments made in the area of medical diagnosis and deep learning application for heart disease diagnosis. The application, database and the learning system used in the automation process is reviewed and outlined the evolution of deep learning approach for medical data analysis.