Abstract
Abstract: Coronary artery disease (CAD) continues to be the primary cause of mortality and chronic impairment in cardiovascular illnesses around the globe, hence coronary artery disease prediction is becoming more important in today's society. As we know, more individuals died as a result of late detection of cardiac disease, thus anticipating it in the early stages is critical. As there are more techniques to predict heart disease but, they are either time consuming or more expensive. So, our goal is to create a system that can predict the outcome fast, cheaply, and more precisely from our house, from our smart phone camera. We know that facial recognition plays a significant part in human-computer interaction, thus we want to integrate this approach with the medical profession in order to anticipate a condition that contributes significantly to the world population's mortality rate. The goal of this review paper is to compare these approaches to the current state-of-the-art and to discuss the challenges that must be addressed. It also includes recommendations for further study.
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