Artificial intelligence in the diagnosis and management of arrhythmias

• Published in: European heart journal Vol. 42; no. 38; pp. 3904 - 3916
• Main Authors: Nagarajan, Venkat D, Lee, Su-Lin, Robertus, Jan-Lukas, Nienaber, Christoph A, Trayanova, Natalia A, Ernst, Sabine
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 07.10.2021
• Subjects: Artificial Intelligence; Atrial Fibrillation - diagnosis; Atrial Fibrillation - therapy; Big Data; Electrocardiography; Humans; State of the Art Review; Electrophysiology; Artificial intelligence; Ablation; Atrial fibrillation; Machine learning
• ISSN: 0195-668X; 1522-9645
• DOI: 10.1093/eurheartj/ehab544

Abstract The field of cardiac electrophysiology (EP) had adopted simple artificial intelligence (AI) methodologies for decades. Recent renewed interest in deep learning techniques has opened new frontiers in electrocardiography analysis including signature identification of diseased states. Artificial intelligence advances coupled with simultaneous rapid growth in computational power, sensor technology, and availability of web-based platforms have seen the rapid growth of AI-aided applications and big data research. Changing lifestyles with an expansion of the concept of internet of things and advancements in telecommunication technology have opened doors to population-based detection of atrial fibrillation in ways, which were previously unimaginable. Artificial intelligence-aided advances in 3D cardiac imaging heralded the concept of virtual hearts and the simulation of cardiac arrhythmias. Robotics, completely non-invasive ablation therapy, and the concept of extended realities show promise to revolutionize the future of EP. In this review, we discuss the impact of AI and recent technological advances in all aspects of arrhythmia care. Graphical Abstract Artificial intelligence-enhanced arrhythmia care.