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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

Datasets

AUROC

Sensitivity

Specificity

PPV

NPV

Training set (TCGA, N = 176)

0.969

0.915

0.884

0.741

0.966

Validation set (GSE21257, N = 53)

0.907

0.857

0.778

0.882

0.737

  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