Machine learning model-based prediction of postpancreatectomy acute pancreatitis following pancreaticoduodenectomy: A retrospective cohort study

Figure 3 Evaluating the performance of six different machine learning algorithms using preoperative and postoperative variables in both training and testing datasets to predict postpancreatectomy acute pancreatitis. A: Receiver operating characteristic curves of six machine learning algorithms in the training dataset; B: Receiver operating characteristic curves of six machine learning algorithms in the testing dataset. ROC: Receiver operating characteristic curves; AUC: Area under the receiver operating characteristic curve; LR: Logistic regression; RF: Random forest; GBDT: Gradient boosting decision tree; LGBM: Light gradient boosting machine; XGB: Extreme gradient boosting; CB: Category boosting.