Authors: Kiran Kumar, V. Narmada, Sagarika Kulkarni
Abstract: Cardiovascular diseases cause morbidity and mortality. Early detection is critical, as it can detect and the use of AI plays a significant role in and impacts cardiovascular diseases. Since cardiovascular diseases (CVDs) continue to be the world's leading cause of death, improvements in early diagnosis, treatment, and management techniques are vital. The integration of artificial intelligence (AI), machine learning, and deep learning into cardiovascular medicine offers promising avenues to improve patient outcomes. This review explores recent progress in AI applications for CVDs, including automated electrocardiogram (ECG) analysis, medical imaging, wearable sensor technologies, and telemedicine. AI-driven systems have demonstrated potential in enhancing diagnostic accuracy, enabling remote monitoring, predicting disease risk, and supporting clinical decision-making. Despite significant advancements, challenges such as data bias, algorithmic fairness, and the need for rigorous clinical validation remain. Continued research and the responsible deployment of AI technologies can help address the global burden of CVDs through more precise, efficient, and personalized care
DOI: https://doi.org/10.5281/zenodo.16719088
