Cardiovascular disease (CVD) is the leading cause of death globally and human ageing is a primary risk factor for its development and progression. Better understanding of the risk factors and disease mechanisms could have major public health impact in terms of prevention and/or new treatments. The goal of the project is to extract novel features from cardiac MRI using deep learning and other machine learning methods, and to understand how these features change with the age of participants. These will be linked to other data in the UK Biobank to identify genetic and environmental factors associated with cardiovascular aging.
