Highlights Gradient Boosting Machine and Random Forest models were built for prediction of mortality at cardiac intensive care units. A total of 9,761 intensive care unit stays of patients admitted under a Cardiac Surgery and Cardiac Medical services were studied. The AUROC and AUPRC values were significantly superior to seven conventional systems compared. The machine learning models’ calibration curves were substantially closer to the ideal line. ABSTRACT Objective: Logistic Regression has been used traditionally for the development of most predictor […]