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Table 1 The performance evaluation of a SVM classifier in training and validation dataset

From: A novel risk score model based on eight genes and a nomogram for predicting overall survival of patients with osteosarcoma

 ROC
DatasetsAUROCSensitivitySpecificityPPVNPV
Training set (TCGA, N = 176)0.9690.9150.8840.7410.966
Validation set (GSE21257, N = 53)0.9070.8570.7780.8820.737
  1. SVM Support vector machine, ROC Receiver operating characteristic, AUROC Area under the receiver operating characteristic curve, PPV Positive predictive value, NPV Negative predictive value