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) |