ABSTRACT
Heart disease is one of the harmful diseases in the world. Coronary heart disease (CHD) happens due to fat deposits on coronary wall and it reduces blood flow to the heart, which leads to heart attack. Heart attack is still the leading cause of death in India. The nature of the proposed work is to predict the disease as early as possible to save the patient’s life. The proposed work develops a deep learning (DL)–based self-learning model for diagnosing heart attack (myocardial infarction [MI]) to prevent the life from death. The chapter is proposed to use a convolutional neural network (CNN) for predicting MI using computed tomography (CT) with a new biomarker called fat attenuation index (FAI). It recommends the medical practitioners to detect the future fatal heart attack many years before it happens.
