Preoperative prediction of textbook outcome in intrahepatic cholangiocarcinoma by interpretable machine learning: A multicenter cohort study

Figure 1 The area under the curve of EXtreme Gradient Boosting model. A: The results showed that the EXtreme Gradient Boosting (XGBoost) model has good prediction effect in the train group [area under the curve (AUC) = 0.882]; B: The XGboost model has good prediction effect in validation group (AUC = 0.834). AUC: Area under the curve.