(untitled) (Modern American Journal of Medical and Health Sciences, 2026)
Cardiovascular diseases (CVDs) remain the leading cause of mortality and disability worldwide, posing a significant burden on healthcare systems and national economies. Early diagnosis, continuous monitoring, and timely clinical intervention are essential for reducing cardiovascular morbidity and mortality. In recent years, artificial intelligence (AI) has emerged as a transformative technology in cardiology, offering innovative solutions for disease detection, risk prediction, medical image interpretation, and patient management. This study investigates the role of artificial intelligence in cardiovascular disease diagnosis and patient monitoring. Particular attention was given to machine learning algorithms, deep learning models, electrocardiogram (ECG) analysis, cardiac imaging technologies, wearable monitoring devices, and telecardiology systems. The potential of AI-based technologies to improve diagnostic accuracy, facilitate early detection of cardiovascular abnormalities, and optimize clinical decision-making was evaluated.