Table 5 Results on the full miRNA-disease datasets in LODOCV.

From: A deep ensemble model to predict miRNA-disease association

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

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