Table 5.

Results on the full miRNA-disease datasets in LODOCV.

Method	AUC	AUPR
RLSMDA	0.8530 ± 0.133	0.2066 ± 0.240
HGIMDA	0.7616 ± 0.164	0.1025 ± 0.142
NCPMDA	0.6374 ± 0.220	0.0596 ± 0.104
PBMDA	0.6902 ± 0.223	0.2918* ± 0.289
RKNNMDA	0.5680 ± 0.131	0.2085 ± 0.273
DeepMDA	0.8729* ± 0.118	0.2556 ± 0.271
SAE + ADA	0.8552 ± 0.124	0.1914 ± 0.220
RAW + DNN	0.8633 ± 0.121	0.2180 ± 0.248

The AUC and AUPR scores are listed above. Generally, DeepMDA performed better than the other seven models in LODOCV.