Figure 1.

Bootstrapped test-set ROC-AUC of all models trained to predict postoperative mRS > 2, sorted by mean ROC-AUC. QDA is the top-performing model, and LR represents the logistic regression baseline model (both highlighted). mRS = modified Rankin Scale, ROC-AUC = area under Receiver Operating Characteristic curve, QDA = quadratic discriminant analysis, ET = Extremely Randomized Trees, SVM = support vector machine, LDA = linear discriminant analysis, XGB = extreme gradient boosting, RF = Random Forest, KNN = k-nearest neighbors, GAM = generalized additive model, MLP = Multilayer Perceptron.