From: DFFNDDS: prediction of synergistic drug combinations with dual feature fusion networks
Method | ACC | BACC | Prec | Rec | F1 | ROC AUC | MCC | Kappa | AP |
---|---|---|---|---|---|---|---|---|---|
DFFNDDS | 0.635(0.014) | 0.605(0.015) | 0.662(0.02) | 0.783(0.023) | 0.717(0.011) | 0.671(0.019) | 0.224(0.026) | 0.217(0.030) | 0.745(0.027) |
DeepDDS | 0.638(0.004) | 0.590(0.002) | 0.659(0.006) | 0.825(0.009) | 0.733(0.006) | 0.651(0.008) | 0.204(0.006) | 0.192(0.005) | 0.722 (0.018) |
DeepSynergy | 0.606(0.006) | 0.564(0.017) | 0.628(0.009) | 0.807(0.034) | 0.706(0.010) | 0.609(0.011) | 0.147 (0.032) | 0.136(0.033) | 0.679(0.012) |
MRGNN | 0.648(0.010) | 0.619(0.009) | 0.685(0.014) | 0.765(0.010) | 0.723(0.011) | 0.694(0.014) | 0.248(0.019) | 0.245(0.019) | 0.775(0.018) |
GCNBMP | 0.623(0.024) | 0.565(0.023) | 0.651(0.012) | 0.732(0.022) | 0.730(0.022) | 0.607 (0.017) | 0.134(0.010) | 0.132(0.008) | 0.702(0.025) |
EPGCNDS | 0.620(0.010) | 0.559(0.005) | 0.649(0.013) | 0.829(0.03) | 0.728(0.014) | 0.625(0.008) | 0.139(0.006) | 0.128(0.008) | 0.725(0.016) |
MatchMaker | 0.609(0.006) | 0.537(0.014) | 0.632(0.015) | 0.867(0.071) | 0.729(0.019) | 0.574(0.018) | 0.100(0.022) | 0.082(0.028) | 0.664(0.019) |