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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