Table 3 Performance of Various Modules of MOSAE
From: A multi-omics supervised autoencoder for pan-cancer clinical outcome endpoints prediction
Methods | OS | DSS | PFI | DFI |
|---|---|---|---|---|
Plain autoencoder | 0.7632 (±0.0058) | 0.7660 (±0.0229) | 0.6999 (±0.0103) | 0.6615 (±0.0340) |
MO + Cat | 0.7644 (±0.0135) | 0.7709 (±0.0292) | 0.7030 (±0.0115) | 0.6634 (±0.0366) |
MO + Ave | 0.7682 (±0.0134) | 0.7753 (±0.0291) | 0.7189 (±0.0136) | 0.6942 (±0.0368) |
MO + Ave + Sup | 0.7721 (±0.0112) | 0.7793 (±0.0252) | 0.7227 (±0.0124) | 0.6960 (±0.0388) |
MO + Ave + Sup + Spec | 0.7830 (±0.0081) | 0.7870 (±0.0293) | 0.7325 (±0.0123) | 0.7061 (±0.0393) |