UKB
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Cardiac phenotype prediction | UKB dataset (test) | LVEDV MAE9.23 | 31 | |
| Multimodal Classification | UKB | AUROC0.8054 | 21 | |
| Age Regression | UKB | MAE0.466 | 20 | |
| Brain Network Classification | UKB BOLD (test) | Accuracy99.59 | 16 | |
| Brain Network Classification | UKB CORR (test) | Accuracy99.22 | 16 | |
| Predictive Modeling | UKB | Accuracy94.6 | 12 | |
| Image Retrieval | UKB | Score (top-4)3.91 | 12 | |
| Active Modality Acquisition | UKB | AUROC1.141 | 11 | |
| Classification | UKB Sex | Accuracy94.89 | 10 | |
| Age Prediction | UKB | Mean Balanced Accuracy0.3391 | 8 | |
| Age Prediction | UKB-Age | Balanced Accuracy33.91 | 8 | |
| Brain network classification | UKB | Average Rank1.8 | 8 | |
| ECG Interpretation | UKB Tier 1 (test) | PRAUC36.7 | 7 | |
| Next disease prediction | UKB longitudinal subset (val) | F1 Score (Brain)65.14 | 6 | |
| ECG-based LVEF classification | UKB (External) | AUROC72.9 | 6 | |
| Cine CMR video generation | UKB (test) | LPIPS0.27 | 6 | |
| Intelligence Regression | UKB | MSE0.992 | 6 | |
| Anomaly Segmentation | UKB (test) | DICE0.232 | 6 | |
| Fluid Intelligence Regression | UKB | MAE1.46 | 5 | |
| Retrieval | UKB-Union | Top-1 Accuracy60 | 5 | |
| Retrieval | UKB | Top-1 Accuracy68.19 | 5 | |
| Fluid Intelligence Status Classification | UKB | Accuracy82.95 | 3 | |
| Age Group Classification | UKB | Accuracy81.58 | 3 | |
| Spatial detection | UKB real brain 182×218×182, N=500 | Runtime (s)5.3 | 3 | |
| fMRI time series classification | UKB Sex | Balanced Accuracy87.52 | 3 |
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