Noninvasive prediction of esophagogastric varices in hepatitis B: An extreme gradient boosting model based on ultrasound and serology

Figure 3 Curves for various prediction metrics across all models. A: Receiver operating characteristic curves; B: Decision curve analysis curves; C: Area under the curve values corresponding to different numbers of features. AUC: Area under the curve; RF: Random forest; AdaBoost: Adaptive boosting; ANN: Artificial neural network; DT: Decision tree; ET: Extra trees; GBM: Gradient boosting machine; KNN: K-nearest neighbors; LightGBM: Light gradient boosting machine; LR: Logistic regression; SVM: Support vector machine; XGB: Extreme gradient boosting.