An Explainable Artificial Intelligence Approach for Discovering Social Determinants of Health and Risk Interactions for Stroke in Patients With Atrial Fibrillation

Stroke remains the primary source of morbidity and mortality associated with atrial fibrillation (AF), despite major advances in prevention. Although effective stroke-prevention strategies are available, optimal implementation of these treatments is limited by (1) rudimentary stroke risk stratification tools (i.e., CHADS2-VA2Sc), and (2) disparities in care and outcomes of AF. Over 150,000 yearly strokes in the United States occur in patients with AF.1 Many of these occur in patients with AF who are misclassified as low-risk or fail to receive appropriate therapies because of healthcare disparities.
Source: The American Journal of Cardiology - Category: Cardiology Authors: Source Type: research