Multiple Instance Learning on TCGA-ESCA
93.7AccuracyAINet
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| AINetBackbone=PLIP2026.02 | 93.7 | 98.2 | 94.5 | |
| DTFD-AFSBackbone=PLIP2026.02 | 92.9 | 97.8 | 94 | |
| ACMILBackbone=PLIP2026.02 | 92.9 | 97.8 | 94 | |
| ABMILBackbone=PLIP2026.02 | 92.3 | 97.6 | 93.4 | |
| CLAMBackbone=PLIP2026.02 | 91.7 | 97.3 | 92.9 | |
| SSMMILBackbone=PLIP2026.02 | 91.7 | 97.5 | 93 | |
| DTFD-MaxMBackbone=PLIP2026.02 | 91.1 | 98.1 | 92.7 | |
| DSMILBackbone=PLIP2026.02 | 90.4 | 96.1 | 91.9 | |
| TransMILBackbone=PLIP2026.02 | 90.4 | 97.8 | 92 | |
| MHIM-ABMILBackbone=PLIP2026.02 | 90.4 | 97.9 | 92 | |
| ILRABackbone=PLIP2026.02 | 89.2 | 96.5 | 90 | |
| WIKGBackbone=PLIP2026.02 | 89.2 | 94.9 | 90 | |
| PAMoEBackbone=PLIP2026.02 | 89.2 | 95.5 | 91.1 | |
| MambaMILBackbone=PLIP2026.02 | 89.1 | 97.7 | 91 | |
| MHIM-TransBackbone=PLIP2026.02 | 88 | 94.7 | 89 | |
| AINetBackbone=ResNet182026.02 | 87.3 | 94.6 | 89.4 | |
| ACMILBackbone=ResNet182026.02 | 86.6 | 93.2 | 89.3 | |
| DTFD-AFSBackbone=ResNet182026.02 | 86.5 | 91.2 | 88.1 | |
| MambaMILBackbone=ResNet182026.02 | 86 | 94.4 | 88.6 | |
| MHIM-TransBackbone=ResNet182026.02 | 85.3 | 91.1 | 87.9 | |
| MHIM-ABMILBackbone=ResNet182026.02 | 82.8 | 91.1 | 86.6 | |
| CLAMBackbone=ResNet182026.02 | 82.1 | 91.6 | 84.4 | |
| DTFD-MaxMBackbone=ResNet182026.02 | 82.1 | 91.4 | 85.1 | |
| ABMILBackbone=ResNet182026.02 | 81.5 | 88.2 | 85.2 | |
| TransMILBackbone=ResNet182026.02 | 81.5 | 87.8 | 84.7 | |
| ILRABackbone=ResNet182026.02 | 80.3 | 89.6 | 83.8 | |
| PAMoEBackbone=ResNet182026.02 | 80 | 89.7 | 83.6 | |
| SSMMILBackbone=ResNet182026.02 | 78.3 | 89.2 | 82.3 | |
| WIKGBackbone=ResNet182026.02 | 77 | 87.4 | 79.3 | |
| DSMILBackbone=ResNet182026.02 | 71.2 | 82.3 | 77.3 |