Artificial intelligence (AI) technologies continue to rapidly transform healthcare delivery, with cardiovascular medicine being one of the highly significantly impacted specialties. This review not only examines the evolving landscape of AI applications in cardiovascular care, but also covers other subspecialities as diagnostic imaging, electrophysiology, interventional cardiology, and preventive medicine. Deep learning has not only enabled remarkable progress in the fields of image analysis, risk stratification, and support for clinical decision. Despite the significant technological developments, major challenges remain in aspects of clinical validation, its integration with existing workflows, and addressing ethical and regulatory concerns. As maturity is noticed for AI systems, its potential to enhance across spheres of diagnostic accuracy, improve patient outcomes, and optimize resource allocation in cardiovascular care is becoming more evident. This review provides a comprehensive analysis of the current state, future directions, and different subspecialty applications of AI in cardiac care ecosystem, to highlight both technological innovations and implementation considerations for the cardiovascular medicine.
Kumar et al. (Mon,) studied this question.