Figure 1.

(A) Performance of different machine learning (ML) models (test set; n = 3152 inpatient cases) and variable importance for random forest (RF) and LASSO. (B) The learned variable importance for the RF model trained on all inpatient cases. (C) The learned variable importance for the LASSO model trained on all inpatient cases. A list with explanations of variable names can be found in the Supplementary Appendix. AUC: area under the receiver-operating characteristic curve; FPR: false positive rate (specificity); TPR: true positive rate (sensitivity).