Table 2.
Comparison with the state-of-the-art algorithms for multi-omics data classification. The bold texts indicate the best performance.
| Dataset | ROSMAP |
LGG |
||||
|---|---|---|---|---|---|---|
| ACC | F1 | AUC | ACC | F1 | AUC | |
|
| ||||||
| KNN | 65.7 ± 3.6 | 67.1 ± 4.5 | 70.9 ± 4.5 | 72.9 ± 3.4 | 73.8 ± 3.8 | 79.9 ± 3.8 |
| SVM | 77.0 ± 2.4 | 77.8 ± 2.6 | 77.0 ± 2.6 | 75.4 ± 4.6 | 75.7 ± 4.6 | 75.4 ± 4.6 |
| LR | 69.4 ± 3.7 | 73.0 ± 3.5 | 77.0 ± 3.5 | 76.1 ± 1.8 | 76.7 ± 2.7 | 82.3 ± 2.7 |
| RF | 72.6 ± 2.9 | 73.4 ± 1.9 | 81.1 ± 1.9 | 74.8 ± 1.2 | 74.2 ± 1.0 | 82.3 ± 1.0 |
| NN | 75.5 ± 2.1 | 76.4 ± 2.5 | 82.7 ± 2.5 | 73.7 ± 2.3 | 74.8 ± 3.7 | 81.0 ± 3.7 |
| GRridge | 76.0 ± 3.4 | 76.9 ± 2.3 | 84.1 ± 2.3 | 74.6 ± 3.8 | 75.6 ± 4.4 | 82.6 ± 4.4 |
| BPLSDA | 74.2 ± 2.4 | 75.5 ± 2.5 | 83.0 ± 2.5 | 75.9 ± 2.5 | 73.8 ± 2.3 | 82.5 ± 2.3 |
| BSPLSDA | 75.3 ± 3.3 | 76.4 ± 2.1 | 83.8 ± 2.1 | 68.5 ± 2.7 | 66.2 ± 2.6 | 73.0 ± 2.6 |
| MOGONET | 81.5 ± 2.3 | 82.1 ± 1.2 | 87.4 ± 1.2 | 81.6 ± 1.6 | 81.4 ± 2.7 | 84.0 ± 2.7 |
| TMC | 82.5 ± 0.9 | 82.3 ± 0.6 | 88.5 ± 0.6 | 81.9 ± 0.8 | 81.5 ± 0.4 | 87.1 ± 0.4 |
| CF | 78.4 ± 1.1 | 78.8 ± 0.5 | 88.0 ± 0.5 | 81.1 ± 1.2 | 82.2 ± 0.4 | 88.1 ± 0.4 |
| GMU | 77.6 ± 2.5 | 78.4 ± 1.6 | 86.9 ± 1.6 | 80.3 ± 1.5 | 80.8 ± 1.2 | 88.6 ± 1.2 |
| MMDynamics | 84.2 ± 1.3 | 84.6 ± 0.7 | 91.2 ± 0.7 | 83.3 ± 1.0 | 83.7 ± 0.4 | 88.5 ± 0.4 |
| UIMC | 87.1 ± 0.0 | – | – | – | – | – |
| MLCLNet | 84.4 ± 1.5 | 85.2 ± 1.5 | 89.3 ± 1.1 | 83.5 ± 1.4 | 84.0 ± 1.3 | 88.6 ± 1.2 |
| KGCCA | 69.5 ± 0.0 | 68.0 ± 0.0 | 69.7 ± 0.0 | 75.7 ± 0.0 | 73.7 ± 0.0 | 75.9 ± 0.0 |
| SCCA | 81.0 ± 0.0 | 81.1 ± 0.0 | 81.0 ± 0.0 | 78.3 ± 0.0 | 78.7 ± 0.0 | 78.3 ± 0.0 |
| MVAE | 75.2 ± 2.6 | 75.0 ± 3.1 | 75.3 ± 2.5 | 82.6 ± 1.6 | 82.5 ± 1.6 | 82.7 ± 1.6 |
| CPM | 74.2 ± 2.4 | 72.9 ± 2.7 | 74.1 ± 2.4 | 76.8 ± 2.9 | 75.8 ± 5.3 | 76.8 ± 3.0 |
| DCP | 78.5 ± 0.0 | 80.5 ± 0.0 | 78.6 ± 0.0 | 79.4 ± 0.0 | 73.4 ± 0.0 | 77.8 ± 0.0 |
| LHGN | 75.9 ± 1.5 | 75.6 ± 2.3 | 76.0 ± 1.5 | 79.9 ± 1.5 | 80.3 ± 1.3 | 79.9 ± 1.6 |
| CLCLSA | 83.0 ± 0.6 | 83.6 ± 0.9 | 88.3 ± 0.0 | 85.0 ± 0.1 | 85.4 ± 0.4 | 90.6 ± 0.7 |
| Dataset | BRCA | KIPAN | ||||
| ACC | F1 | AUC | ACC | F1 | AUC | |
| KNN | 74.2 ± 2.4 | 68.2 ± 2.5 | 73.0 ± 2.5 | 96.7 ± 1.1 | 96.0 ± 1.4 | 96.7 ± 1.1 |
| SVM | 72.9 ± 1.8 | 64.0 ± 1.7 | 70.2 ± 1.7 | 99.5 ± 0.3 | 99.4 ± 0.4 | 99.5 ± 0.3 |
| LR | 73.2 ± 1.2 | 64.2 ± 2.6 | 69.8 ± 2.6 | 97.4 ± 0.2 | 97.2 ± 0.4 | 97.4 ± 0.2 |
| RF | 75.4 ± 0.9 | 64.9 ± 1.3 | 73.3 ± 1.3 | 98.1 ± 0.6 | 97.5 ± 1.1 | 98.1 ± 0.6 |
| NN | 75.4 ± 2.8 | 66.8 ± 4.7 | 74.0 ± 4.7 | 99.1 ± 0.5 | 99.1 ± 0.5 | 99.1 ± 0.5 |
| GRridge | 74.5 ± 1.6 | 65.6 ± 2.5 | 72.6 ± 2.5 | 99.4 ± 0.4 | 99.3 ± 0.4 | 99.4 ± 0.4 |
| BPLSDA | 64.2 ± 0.9 | 36.9 ± 1.7 | 53.4 ± 1.7 | 93.3 ± 1.3 | 91.9 ± 2.1 | 93.3 ± 1.3 |
| BSPLSDA | 63.9 ± 0.8 | 35.1 ± 2.2 | 52.2 ± 2.2 | 91.9 ± 1.2 | 89.5 ± 1.4 | 91.8 ± 1.3 |
| MOGONET | 82.9 ± 1.8 | 77.4 ± 1.7 | 82.5 ± 1.7 | 99.9 ± 0.2 | 99.9 ± 0.2 | 99.9 ± 0.2 |
| TMC | 84.2 ± 0.5 | 80.6 ± 0.9 | 84.4 ± 0.9 | 99.7 ± 0.3 | 99.4 ± 0.5 | 99.7 ± 0.3 |
| CF | 81.5 ± 0.8 | 77.1 ± 0.9 | 81.5 ± 0.9 | 99.2 ± 0.5 | 98.8 ± 0.9 | 99.2 ± 0.5 |
| GMU | 80.0 ± 3.9 | 74.6 ± 5.8 | 79.8 ± 5.8 | 97.7 ± 1.6 | 95.8 ± 3.2 | 97.6 ± 1.7 |
| MMDynamics | 87.7 ± 0.3 | 84.5 ± 0.5 | 88.0 ± 0.5 | 99.9 ± 0.2 | 99.9 ± 0.3 | 99.9 ± 0.2 |
| UIMC | 82.9 ± 0.0 | – | – | – | – | – |
| MLCLNet | 86.4 ± 1.6 | 82.6 ± 1.8 | 87.8 ± 1.6 | 99.9 ± 0.7 | 99.2 ± 0.2 | 99.2 ± 0.2 |
| KGCCA | 73.3 ± 0.0 | 62.5 ± 0.0 | 71.0 ± 0.0 | 93.4 ± 0.0 | 88.3 ± 0.0 | 93.1 ± 0.0 |
| SCCA | 81.7 ± 0.0 | 76.8 ± 0.0 | 81.7 ± 0.0 | 93.9 ± 0.0 | 88.6 ± 0.0 | 93.6 ± 0.0 |
| MVAE | 75.9 ± 3.6 | 65.3 ± 5.2 | 73.4 ± 5.0 | 93.7 ± 1.5 | 92.9 ± 1.7 | 93.6 ± 1.6 |
| CPM | 78.0 ± 2.3 | 75.0 ± 2.4 | 78.4 ± 2.2 | 96.0 ± 1.9 | 95.3 ± 1.9 | 96.0 ± 1.9 |
| DCP | 81.7 ± 0.0 | 74.9 ± 0.0 | 82.3 ± 0.0 | 97.0 ± 0.0 | 94.7 ± 0.0 | 97.0 ± 0.0 |
| LHGN | 80.8 ± 0.6 | 76.6 ± 1.1 | 80.8 ± 0.7 | 99.0 ± 0.3 | 98.4 ± 0.7 | 99.0 ± 0.3 |
| CLCLSA | 87.5 ± 1.0 | 85.6 ± 0.6 | 87.8 ± 0.3 | 99.9 ± 0.3 | 99.9 ± 0.3 | 99.9 ± 0.3 |