Advancing Cardiovascular Disease Risk Prediction in Older People: Leveraging AI-Driven Approaches for Risk Prediction, Causal Inference, and Identification of Disease Clusters

Clinical, behavioural, and social factors, like lower income, being alone, and poor social support increases the risk of cardiovascular disease. But most tools used today to check cardiovascular disease risk do not include social factors. This thesis uses artificial intelligence methods to integrate social factors with clinical and behavioural factors to predict cardiovascular disease risk, paying special attention to a gender-disaggregated analyses. The findings show that social factors are strong predictors of cardiovascular disease risk. For women, they matter more than clinical and behavioural factors. Ultimately, this thesis offers a better, earlier way to prevent cardiovascular disease.