Application of Artificial Intelligence in the Early Detection and Management of Atrial Fibrillation: State-of-the-art Review

AF is the most common cardiac arrhythmia in clinical practice, with a significant impact on morbidity, mortality and healthcare costs. Optimal management of AF requires a multidimensional approach that includes early and accurate diagnosis, the choice between rate and rhythm control strategies and the integrated management of associated comorbidities. In the age of artificial intelligence (AI), a new paradigm in AF care is emerging, thanks to innovative tools capable of supporting clinicians throughout all phases of the diagnostic and therapeutic journey. AI-based algorithms can improve diagnostic accuracy through the analysis of standard ECGs or wearable devices, predict arrhythmic events or complications and guide personalised therapeutic decisions. Furthermore, the integration of AI into healthcare systems enables more efficient management of comorbidities, promoting a holistic and proactive approach. This review explores the potential of, and challenges involved in, using AI in the management of AF, outlining a future scenario in which the technology can amplify clinical expertise and improve patient outcomes.