A Review of the Scope, Future, and Effectiveness of Using Artificial Intelligence in Cardiac Rehabilitation: A Call to Action for the Kingdom of Saudi Arabia

Abstract

The burden of cardiovascular disease (CVD) is still rising after decades of growth. CVD is the leading cause of death in the Kingdom of Saudi Arabia (KSA), accounting for more than 45% of all CVD-related deaths. The development of cardiac rehabilitation (CR) programs is significantly aided by artificial intelligence (AI) approaches, including machine learning and deep learning models. However, the KSA has a limited supply of CR, and AI methods are unavailable. This review aims to assess contemporary research on AI approaches’ application, potential, and efficacy in CR as a call to action for harnessing it in the KSA. Using the keywords artificial intelligence, AI, machine learning, deep learning models, cardiac rehabilitation, and Saudi Arabia, electronic databases of PubMed, CINHAL, Web of Science, PEDro, and SCOPUS were searched to find relevant articles. Evidence from the literature supports the idea that using AI techniques in CR can improve the ability to effectively diagnose more patients in areas without doctors in Saudi Arabia. Using AI in CR has constrained CR resources, which will lessen the need for outsourcing and enhance healthcare. Patients can receive an accurate diagnosis online thanks to machine learning algorithms and the expanding capabilities of AI.