Tau-progression forecasting on ADNI All-68-region (test)
0.78Mean Absolute Error (MAE)Tekkesinoglu et al.
Evaluation Results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| Tekkesinoglu et al.Type=Graph learning2026.06 | 0.78 | 0.62 | 0.98 | 89 | 0.53 | 0.62 | |
| BN-LTEType=Ours2026.06 | 0.89 | 0.84 | 0.94 | 95 | 0.72 | 0.88 | |
| Karlsson et al.Type=Machine Learning2026.06 | 0.9 | 0.7 | 0.98 | 92 | 0.73 | 0.78 | |
| BN-LTE + ATN-Z tau-freeType=Ours2026.06 | 0.91 | 0.82 | 0.92 | 92 | 0.52 | 0.83 | |
| Ren et al.Type=Graph Learning2026.06 | 0.98 | 0.54 | 0.98 | 90 | 0.67 | 0.83 | |
| Iturria-Medina et al.Type=Biophysical2026.06 | 1.04 | 0.76 | 0.92 | 96 | 0.64 | 1.01 | |
| BN-LTE + PCA-ZType=Ours2026.06 | 1.04 | 0.81 | 0.91 | 93 | 0.48 | 1.05 | |
| Raj et al.Type=Biophysical2026.06 | 1.05 | 0.77 | 0.91 | 94 | 0.64 | 0.94 | |
| Ozdemir et al.Type=Graph learning2026.06 | 1.05 | 0.57 | 0.98 | 92 | 0.53 | 0.92 | |
| Schafer et al.Type=Bayesian/Biophysical2026.06 | 1.11 | 0.76 | 0.89 | 94 | 0.72 | 0.88 | |
| Giorgio et al.Type=Machine Learning2026.06 | 1.17 | 0.64 | 0.98 | 90 | 0.6 | 1.02 | |
| Rathore et al.Type=Machine Learning2026.06 | 1.24 | 0.49 | 0.97 | 89 | 0.33 | 1.06 | |
| Jasodanand et al.Type=Deep learning2026.06 | 1.43 | 0.22 | 0.93 | 80 | 0.4 | 0.85 | |
| Nguyen et al.Type=Deep learning2026.06 | 2.51 | 0.3 | 0.91 | 86 | 0.27 | 1.91 | |
| Tabarestani et al.Type=Deep learning2026.06 | 4.52 | 0.09 | 0.77 | 73 | 0.27 | 2.89 |