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Table 4 Comparison with multiple evaluation metrics

From: CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network

DATASET

AUC

AUPR

F1

MCC

ACC

RECALL

GCMDR

0.6882

0.1203

0.9543

0.0806

0.2002

0.0420

AE-RF

0.8653

0.8062

0.7436

0.7359

0.4928

0.7870

GCNMDA

0.7714

0.1465

0.9403

0.1485

0.1311

0.1092

SIMCCDA

0.8291

0.1756

0.6839

0.1992

0.0083

0.2358

VGAELDA

0.5114

0.6367

0.8364

0.0370

0.1255

0.0188

GATMDA

0.9254

0.9067

0.8487

0.8604

0.7075

0.9327

CRPGCN

0.9720

0.9418

0.9907

0.8959

0.8940

0.8319

  1. Bold indicates the Area Under the receiver operating characteristic Curve (AUC) is plot by TPR and FPR, and the Area Under Precision-Recall curve (AUPR) is plot by Recall and Precision. Precision = TP/(TP + FN)