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Results for the clinical feature-based models. (Left panel) Average AUCs on the five training splits. (Right panel) Average AUCs on the test splits. SFM SelectFromModel, PCA principal component analysis, CLUSTER feature agglomeration through clustering, SVM support vector machines, BAG bagging, RF random forest, XGB extreme gradient boosting, NNET neural network, NN k-nearest neighbours.
