March 2026 Br J Cardiol 2026;33(1) doi:10.5837/bjc.2026.012 Online First
Ismail Sooltan, Aqib Khan, Rajib Haque, Sudantha Bulugahapitiya
The current landscape of ML in cardiology ML has established a presence across various domains of cardiology practice. In cardiovascular imaging, deep learning algorithms assist in echocardiographic interpretation, supporting functions such as ejection fraction calculation and abnormality detection.7 Advances in cardiac magnetic resonance imaging (MRI) applications have contributed to automating tasks like myocardial segmentation, while ML approaches to coronary computed tomography (CT) analysis aim to improve coronary plaque assessment.4,7 Electrocardiography has also seen ML integration. Algorithms designed to detect arrhythmias and identif
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