Figure 7.

ROC-AUC of all models on both the internal (left column in each subplot) and external (right column in each subplot) test set. One can clearly observe the pronounced performance drop, especially of the model with the highest ROC-AUC on the internal test set. ROC-AUC = area under Receiver Operating Characteristic curve, mRS = modified Rankin Scale, GOS =  Glasgow outcome scale, GAM = Generalized Additive Model, XGB = extreme gradient boosting, ET = Extremely Randomized Trees, k-NN = k-nearest neighbors, LDA = linear discriminant analysis, SVM = support vector machine, LR = logistic regression, MLP = Multilayer Perceptron, QDA = quadratic discriminant analysis, RF = Random Forest.