Researchers at Mount Sinai developed a graph neural network-based artificial intelligence model to better determine which atrial fibrillation patients require blood thinners to prevent stroke. By analyzing extensive electronic health records, the model provides personalized anticoagulation risk assessments, aiming to optimize treatment decisions and reduce stroke incidence. This advance holds transformative potential for improving care and outcomes in the millions affected by AF worldwide.