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Table 4 Performances of NEMII, PBMDA, NTSMDA and GRNMF

From: A network embedding-based multiple information integration method for the MiRNA-disease association prediction

Methods AUPR AUC F1 ACC REC SPEC PRE
NEMII 0.6104 ± 0.0012 0.9293 ± 0.0017 0.6147 ± 0.0025 0.9956 ± 0.0001 0.4893 ± 0.0060 0.9993 ± 0.0001 0.8289 ± 0.0164
PBMDA 0.2095 ± 0.0015 0.9164 ± 0.0005 0.2676 ± 0.0021 0.9892 ± 0.0005 0.2759 ± 0.0139 0.9944 ± 0.0006 0.2642 ± 0.0103
NTSMDA 0.0916 ± 0.0012 0.8857 ± 0.0009 0.1410 ± 0.0013 0.9740 ± 0.0015 0.2988 ± 0.0171 0.9788 ± 0.0017 0.0931 ± 0.0020
GRNMF 0.2446 ± 0.0024 0.9128 ± 0.0008 0.3192 ± 0.0137 0.9945 ± 0.0005 0.2989 ± 0.0127 0.9897 ± 0.0004 0.3066 ± 0.0016