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Table 4 Performance of Model for Comparison

From: Exploring potential circRNA biomarkers for cancers based on double-line heterogeneous graph representation learning

model

accuracy

sensitivity

specificity

precision

MCC

AUROC

AUPR

SIMCCDAA

0.8317

0.7708

0.9965

0.0556

0.1772

0.8802

0.0885

CRPGCN

0.9696

0.6077

0.9988

0.9634

0.7567

0.9387

0.8748

DMCCDA

0.9224

0.0948

0.9993

0.1346

0.3412

0.9881

0.8800

CDA-DGRL (ours)

0.9569 ± 0.0017

0.9462 ± 0.0121

0.9677 ± 0.0138

0.9672 ± 0.1323

0.9143 ± 0.0037

0.9866 ± 0.0022

0.9897 ± 0.0014

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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