Ramin Zand, MD, MPH

Dr. Zand and his colleagues are conducting research focused on using multimodal data—such as electronic health records (EHRs), machine learning (ML), and artificial intelligence (AI)—to improve stroke prediction, outcomes, and care systems. Their work includes developing advanced models to predict stroke recurrence, mortality, and recovery, aiming to personalize treatment and enhance prevention strategies. Additionally, they are addressing stroke health disparities, particularly in rural areas, by analyzing long-term health trends and the challenges faced by these populations, such as limited access to care.