The Mathioudakis lab is focused on developing and evaluating clinical decision support systems, technology, and mHealth for diabetes prevention and management. Our lab leverages large electronic medical record databases and uses machine learning algorithms and artificial intelligence to identify patterns in clinical care associated with optimal clinical outcomes. We are interested in understanding the role that advanced diabetes technologies can play in improving health outcomes for patients with diabetes. Our lab has published extensively on outcomes related to diabetes prevention and diabetes management and outcomes. Based on data from our long-term (over 10 year) clinic-based prospective cohort study from the Johns Hopkins Multidisciplinary Diabetic Foot and Wound Clinic, we have published extensively on clinical predictors and outcomes of patients with diabetic foot ulcers, focusing specifically on the role that glycemic control plays in patients with this complication. Healthcare disparities exist throughout medicine, but are particularly prominent in diabetes; our lab has evaluated healthcare inequities in diabetes outcomes and is developing and evaluating strategies to overcome them. In addition to identify optimal management approach to diabetes and its complications, our lab is interested in development and evaluation of innovative technology approaches to diabetes prevention.