Artificial Intelligence and Digital Innovation in Cardiovascular Medicine

Abstract

Advances in digital innovation and data science are rapidly transforming cardiovascular medicine, with artificial intelligence, machine learning, and digital health tools now moving from experimental applications into clinical practice. This review provides a comprehensive overview of developments across the cardiovascular care continuum, with a particular focus on Asian populations where the burden of disease is high and health care systems face unique challenges. We highlight the role of large-scale cohort studies, risk prediction algorithms, multimodal artificial intelligence models, and digital innovations such as wearable devices and assistive clinical tools in prevention, diagnosis, treatment, and follow-up. Furthermore, we discuss barriers to implementation, including data quality, infrastructure, and regulatory frameworks. By integrating perspectives from laboratory science to bedside practice, this review outlines both the current state of research and the translational pathway required to achieve precision cardiology that is equitable, scalable, and sustainable.

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