Deep learning radiomic analysis in the prediction of MYCN status and survival outcome in children with neuroblastoma

Figure 3 Evaluation of predictive performances for the integrated nomogram model for the prediction of MYCN amplification in neuroblastomas. A: Nomogram model combining significant clinical variables and the deep learning (DL)-based signature. The DL-based signature was generated from the best DL-based model considering the area under the receiver operating characteristic curve (AUC) of the testing cohort among all models; B: Receiver operating characteristic curves for the predictive performance of the nomogram model in the training and testing cohorts, respectively. The AUC of the training cohort was 0.959, and the AUC of the testing cohort was 0.819; C: Curves of the calibration analysis for the nomogram model in the training and testing cohorts, respectively. AUC: Area under the receiver operating characteristic curve; ROC: Receiver operating characteristic; DL: Deep learning.