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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