Developing a synthetic Australian national population to investigate the effectiveness of machine learning techniques for cardiovascular disease risk prediction

Investigate the effectiveness of machine learning techniques for cardiovascular disease risk prediction using an synthetic national population dataset based on data from multiple existing datasets. The development of a large and representative population dataset enables CVD risk prediction for the Australian population as well as for specialized cohorts within the overall population. Received Impact Seed Funding for Early Career Researchers ($ 10,000) for this project.