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Table 3 Comparison of the AUC values and AUPR values of MAGCNSE using GCN and other graph models

From: MAGCNSE: predicting lncRNA-disease associations using multi-view attention graph convolutional network and stacking ensemble model

Method

GAT

GraphSAGE

GCN

AUC

0.9668

0.9713

0.9812

AUPR

0.9713

0.9723

0.9849

Accuracy

0.9045

0.9188

0.9395

Sensitivity

0.8929

0.9231

0.9192

Specificity

0.9156

0.9142

0.9626

Precision

0.9106

0.9202

0.9654

F1- score

0.9016

0.9217

0.9417

MCC

0.8089

0.8374

0.88

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BMC Bioinformatics

ISSN: 1471-2105

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