Mortality Prediction on PhysioNet Challenge 2012
0.868AUROCHyMaTE
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| HyMaTE2025.09 | 0.868 | 0.602 | — | — | |
| DuETT2025.09 | 0.857 | 0.598 | — | — | |
| DuETT2026.06 | 0.857 | 0.598 | — | — | |
| DuETT2026.06 | 0.857 | 0.598 | — | — | |
| Triplet-Mamba2026.06 | 0.851 | 0.59 | — | — | |
| Triplet-Mamba2026.06 | 0.851 | 0.59 | — | — | |
| EHR-Mamba2025.09 | 0.844 | 0.534 | — | — | |
| EHR-Mamba2026.06 | 0.844 | 0.534 | — | — | |
| EHR-Mamba2026.06 | 0.844 | 0.534 | — | — | |
| GRU-D2026.06 | 0.843 | 0.451 | — | — | |
| STraTS2025.09 | 0.838 | 0.487 | — | — | |
| STraTS2026.06 | 0.838 | 0.487 | — | — | |
| STraTS2026.06 | 0.838 | 0.487 | — | — | |
| CfCRank=Full, h=256, backbone units=64, layers=22026.04 | 0.836 | — | 92,930 | 100 | |
| LottaLoRARank=r=2, h=256, backbone units=64, layers=22026.04 | 0.835 | — | 5,292 | 5.7 | |
| LottaLoRARank=r=4, h=256, backbone units=64, layers=22026.04 | 0.834 | — | 8,912 | 9.6 | |
| LottaLoRARank=r=8, h=256, backbone units=64, layers=22026.04 | 0.833 | — | 16,152 | 17.4 | |
| LottaLoRARank=r=1, h=256, backbone units=64, layers=22026.04 | 0.832 | — | 3,482 | 3.7 | |
| GRU2026.06 | 0.818 | 0.407 | — | — | |
| SeFT2025.09 | 0.812 | 0.464 | — | — | |
| SeFT2026.06 | 0.812 | 0.464 | — | — | |
| InterpNet2026.06 | 0.803 | 0.402 | — | — | |
| TCN2026.06 | 0.801 | 0.433 | — | — | |
| SAnD2026.06 | 0.801 | 0.404 | — | — | |
| AID-MAErandom masking=25%2026.02 | 0.782 | 0.393 | — | — | |
| SMART2026.02 | 0.778 | 0.385 | — | — | |
| DuETT2026.02 | 0.777 | 0.388 | — | — | |
| XGBoost2026.02 | 0.769 | 0.369 | — | — | |
| Supervised Transformer2026.02 | 0.767 | 0.341 | — | — | |
| Logistic Regression2026.02 | 0.727 | 0.313 | — | — |