Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma

Figure 4 The area under receiver operating characteristic curve barplot, importance, and heatmap showing expression values of the selected features. The feature importance plot was provided by the random forest methods as soon as the model train procedure completed. The importance of the feature was computed from permuting out-of-bag data. A: The area under receiver operating characteristic curve barplot of the selected predictive radiomics features; B: The importance of the selected predictive radiomics features; C: The heatmap showing expression values of the selected radiomics features (rows) of 71 pancreatic ductal adenocarcinoma patients (columns). AUC: Area under the receiver operating characteristic curve.