Predicting Australian adults at high risk of cardiovascular disease mortality using standard risk factors and machine learning
Effective cardiovascular disease (CVD) prevention relies on timely identification and intervention for individuals at risk. Conventional formula-based techniques have been demonstrated to over-or under-predict the risk of CVD in the Australian population. This study assessed the ability of machine learning models to predict CVD mortality...
Translating a health service intervention into a rural setting: lessons learned
This article discusses the limited existing research on the process of applying knowledge translation methodology to a rural-based population health intervention and a project that attempted to implement a co-created framework to address musculoskeletal conditions in Port Lincoln, South Australia.