From: DFFNDDS: prediction of synergistic drug combinations with dual feature fusion networks
Method | ACC | BACC | Prec | Rec | F1 | ROC AUC | MCC | Kappa | AP |
---|---|---|---|---|---|---|---|---|---|
DFFNDDS | 0.768 (0.002) | 0.749(0.004) | 0.788(0.006) | 0.840(0.009) | 0.813(0.002) | 0.846(0.002) | 0.509(0.005) | 0.507(0.006) | 0.890(0.001) |
DeepDDS | 0.745 (0.003) | 0.710(0.005) | 0.743(0.006) | 0.881 (0.007) | 0.806(0.001) | 0.825(0.002) | 0.455(0.005) | 0.441 (0.008) | 0.876 (0.001) |
DeepSynergy | 0.719(0.001) | 0.692(0.003) | 0.739 (0.006) | 0.826(0.009) | 0.780(0.002) | 0.790(0.003) | 0.401(0.003) | 0.396(0.005) | 0.849 (0.003) |
MRGNN | 0.665(0.003) | 0.631(0.002) | 0.693(0.001) | 0.798(0.011) | 0.742(0.005) | 0.716(0.003) | 0.279(0.005) | 0.273(0.004) | 0.795(0.003) |
GCNBMP | 0.628(0.033) | 0.551(0.012) | 0.635(0.013) | 0.930(0.008) | 0.750(0.001) | 0.587(0.006) | 0.211(0.006) | 0.237(0.001) | 0.679(0.006) |
EPGCNDS | 0.628(0.004) | 0.572(0.003) | 0.645(0.004) | 0.850(0.008) | 0.734(0.004) | 0.647(0.004) | 0.173(0.008) | 0.156(0.007) | 0.733(0.005) |
MatchMaker | 0.695(0.004) | 0.649(0.007) | 0.697(0.005) | 0.874(0.008) | 0.776(0.002) | 0.757(0.004) | 0.340 (0.010) | 0.319(0.010) | 0.824(0.003) |