Dynamic and personalized prediction of complex cardiovascular events.

PROJECT NARRATIVE The objective of this project is to develop novel statistical learning methods for predicting complex time-to-event outcomes such as recurrent events. The proposed methodology will have broad applicability; in particular, we aim to address the gap in predicting cardiovascular disease (CVD) recurrence by analyzing the data from the NHLBI Pooled Cohorts Study. The proposed research has the potential to advance dynamic and personalized risk prediction and to facilitate more effective prevention and treatment strategies for CVD recurrence.