Tag Archives: machine learning

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

Introduction Artificial intelligence (AI) is poised to revolutionise cardiology over the next decade, offering unprecedented potential and exciting advancements. The immense burden of cardiovascular disease in the population provides cardiologists with a huge swathe of rich medical data, yet at the moment this is still underutilised. Machine learning and deep learning are subsets of AI that learn from data, rather than being specifically programmed, to identify new patterns and produce decision-making models.1 From improving diagnostic accuracy to enhancing treatment strategies, machine learning has the power to reshape patient care and outco