Predicting esophageal cancer response to neoadjuvant therapy with magnetic resonance imaging radiomics

Figure 3 Performance evaluation of radiomics models. A and B: Receiver operating characteristic curve analysis comparing model performance in the training (A) and validation cohort (B). AUC: Area under the curve; KNN: K-nearest neighbor; GBM: Light gradient boosting machine; LR: Logistic regression; MLP: Multilayer perceptron; SVM: Support vector machines; XGBoost: Extreme gradient boosting.