Risk Prediction Modelling of Mortality and In-Hospital Major Bleeding Following Percutaneous Coronary Intervention: Machine Learning Approaches

Adverse outcomes such as bleeding and mortality remain important concerns after cardiac procedures like PCI, commonly known as stenting. Risk prediction tools are often used to predict these outcomes before the procedure, helping clinicians make better decisions. However, most existing models were developed overseas and may not be fully applicable to the Australian population due to differences in demographics and healthcare settings. This research focuses on developing machine learning–based risk prediction models to predict the chance of major bleeding and mortality after PCI, using Australian data. These models aim to support personalized care and improve patient outcomes in Australia.