Explainable machine learning model for predicting minor amputation in diabetic foot ulcers

Figure 4 Validation and evaluation of the random forest model. A and B: Receiver operating characteristic curves for the training set (n = 480; area under the receiver operating characteristic curve =0.844) and validation set (n = 205; area under the receiver operating characteristic curve = 0.766), respectively; C and D: Calibration curves for the training set (Brier score = 0.161) and validation set (Brier score = 0.198), respectively; the dashed diagonal line represents ideal calibration; E and F: Decision curve analysis for the training set and validation set, respectively. The Y-axis denotes mean net benefit, and the X-axis denotes threshold probability (%). AUC: Area under the receiver operating characteristic curve; ROC: Receiver operating characteristic.