The Role of Artificial Intelligence in Early Detection of Cardiovascular Diseases

Abstract

Cardiovascular diseases (CVDs) remain one of the leading causes of mortality worldwide, with early detection playing a crucial role in preventing complications and reducing healthcare burdens. This article explores the role of Artificial Intelligence (AI) in the early detection of CVDs, highlighting its potential in improving diagnostic accuracy and streamlining patient care. AI-driven tools, particularly machine learning (ML) algorithms, have shown promising results in the analysis of medical imaging, ECG signals, and patient data, enabling early identification of CVD risk factors such as arrhythmias, coronary artery disease, and heart failure. This paper reviews various AI methodologies, their applications in clinical settings, and the challenges in their widespread implementation. Additionally, it discusses the implications of AI technologies for healthcare systems, patient outcomes, and healthcare cost reduction. The integration of AI in early diagnosis is poised to enhance patient care and significantly improve outcomes for CVD patients.