Author(s) :

Ethan Nguy.

Volume/Issue :

Abstract :

Cardiovascular disease remains one of the leading causes of death worldwide. Early diagnosis of these diseases is crucial to improving patient outcomes. The electrocardiogram (ECG) is a widely used, non-invasive tool to help detect some of these abnormalities by utilizing the electricity the heart conducts. However, traditional ECG interpretation relies on manual analysis and may fail to identify subtle indicators of disease. Recent advancements in artificial intelligence (AI) have enhanced ECG analysis by identifying complex patterns associated with arrhythmias, coronary artery disease, heart failure, and structural heart disease. This review discusses how AI improves the detection, treatment, and monitoring of cardiovascular diseases through ECG-based models, personalized therapy planning, AI-enabled wearables, and telemonitoring systems. This review also explores digital biomarkers, such as AI-derived heart age and vascular age, for continuous risk assessment and monitoring. Ethical and practical challenges–such as data quality, algorithmic bias, privacy, and the need for human oversight– are also covered. Overall, this review highlights AI’s potential to advance preventive, precise, and equitable cardiovascular care.