Artificial intelligence in electrophysiology

Cardiac electrophysiology is rapidly evolving with advancements and applications in artificial intelligence (AI), given the rich level of diverse and high-dimensional data relevant to electrophysiology. AI has been useful to leverage data spanning the spectrum of basic science to clinical medicine including genetic information, atomic and molecular physicochemical features, signal data from action potential recordings and electrocardiograms, computational modeling data, cardiac imaging, and the electronic medical record. In this chapter, we review the current state of the art of AI in electrophysiology, first with its applications in basic science and computational modeling, then within clinical medicine across select disease focuses (atrial fibrillation, ventricular arrhythmia, and cardiac resynchronization therapy). We then outline future directions for AI in electrophysiology. A substantial component of AI in electrophysiology—AI interpretation of the electrocardiogram (ECG)—is discussed in a separate dedicated chapter.