Artificial intelligence algorithms enhance large-scale population-based screening, diagnostic assessments, and treatment pathways for atrial fibrillation.
AF is the most common clinically relevant cardiac arrhythmia associated with multiple comorbidities, cardiovascular complications (e.g. stroke) and increased mortality. As artificial intelligence (AI) continues to transform the practice of medicine, this review article highlights specific applications of AI for the screening, diagnosis and treatment of AF. Routinely used digital devices and diagnostic technology have been significantly enhanced by these AI algorithms, increasing the potential for large-scale population-based screening and improved diagnostic assessments. These technologies have similarly impacted the treatment pathway of AF, identifying patients who may benefit from specific therapeutic interventions. While the application of AI to the diagnostic and therapeutic pathway of AF has been tremendously successful, the pitfalls and limitations of these algorithms must be thoroughly considered. Overall, the multifaceted applications of AI for AF are a hallmark of this emerging era of medicine.
Harmon et al. (Wed,) conducted a review in Atrial Fibrillation. Artificial intelligence was evaluated. Artificial intelligence algorithms enhance large-scale population-based screening, diagnostic assessments, and treatment pathways for atrial fibrillation.