Big Data, Risk Prediction and Epidemiology

Our lab uses big-data approaches to predict risk of heart failure that can be used to identify who may benefit from effective preventive therapies. We have also developed novel risk-prediction models to better predict risk of cardiovascular diseases. This work has been recognized by awards from the American Heart Association Get With The Guidelines – Heart Failure Data Challenge and the National Heart, Lung, and Blood Institute Data Challenge awards. We have published a series of studies establishing the independent role of low fitness and inactivity as a risk factor for heart failure in older adults. This work has been featured in AHA scientific statements advocating for fitness testing to predict cardiovascular risk and contributed to recent guideline recommendations to consider physical inactivity as a modifiable risk factor for heart failure. Additionally, we have investigated the risk of heart failure among patients with diabetes, the prevalence of diabetic cardiomyopathy, and the risk of other cardiovascular conditions among patients with diabetes.