Fig. 4

Calibration (A) and decision curve analysis (B) for a stacked ensemble prediction model based on a multivariable logistic regression, an Elastic Net, a Random Forest and a Gradient Boosting Machine as base learners. The stacked ensemble is based on a Gradient Boosting Machine that predicts the mortality outcome based on the cross-validated predictions of the base learners. For calibration, shaded areas denote the 95%-confidence range and black dashed lines indicate the Generalized Additive Model (GAM)-smoothed calibration belts from the ensemble of 100 individual calibration belts. P-values regarding the quality of the calibration and Brier-scores are shown