Data science to optimize cardiovascular disease prevention

2024

A team of students led by an interdisciplinary group including statistician Fan Li, neurologist Brian Mac Grory, and physician/population health scientist Jay Lusk will integrate information from diverse real-world datasets to better understand risk factors for cardiovascular diseases such as heart attack and stroke. The team will use techniques ranging from classical epidemiology to machine learning for predictive analytics to causal inference to unlock new insights about cardiovascular disease.  This is an ideal project for students interested in big data, predictive modeling, causal inference, healthcare analytics, epidemiology, public health, or careers in medicine. This work is expected to result in high-impact publications in clinical journals and there are diverse opportunities for Data+ participants to take a leadership role in developing the analytical approach. This Data+ project is a companion to a 2024-2025 Bass Connections Project led by Drs. Li, Mac Grory, and Lusk.

Project Leads: Fan Li, Brian Mac Grory, and Jay Lusk

Contact

Mathematics