The Role of Artificial Intelligence in the Prediction, Diagnosis, and Management of Cardiovascular Diseases: A Narrative Review

Abstract

Cardiovascular diseases (CVDs) remain the leading global cause of mortality, and a high prevalence of cardiac conditions, including premature deaths, have increased from decades until today. However, early detection and management of these conditions are challenging, given their complexity, the scale of affected populations, the dynamic nature of the disease process, and the treatment approach. The transformative potential is being brought by Artificial Intelligence (AI), specifically machine learning (ML) and deep learning technologies, to analyze massive datasets, improve diagnostic accuracy, and optimize treatment strategy. The recent advancements in such AI-based frameworks as the personalization of decision-making support systems for customized medicine automated image assessments drastically increase the precision and efficiency of healthcare professionals. However, implementing AI is widely clogged with obstacles, including regulatory, privacy, and validation across populations. Additionally, despite the desire to incorporate AI into clinical routines, there is no shortage of concern about interoperability and clinician acceptance of the system. Despite these challenges, further research and development are essential for overcoming these hurdles. This review explores the use of AI in cardiovascular care, its limitations for current use, and future integration toward better patient outcomes.

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