ADNI
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Alzheimer stage classification | ADNI | Macro F179.64 | 200 | |
| Outlier detection | ADNI (test) | Likelihood Ratio10.2 | 96 | |
| Alzheimer's Disease Classification | ADNI (test) | Accuracy90.6 | 92 | |
| CN vs. MCI vs. AD classification | ADNI | Accuracy72.1 | 72 | |
| Alzheimer's disease diagnosis | ADNI | AUC96 | 60 | |
| Classification | ADNI (test) | Accuracy96.19 | 57 | |
| NC vs. MCI classification | ADNI | Accuracy92.11 | 53 | |
| NC vs. AD classification | ADNI | Accuracy96.8 | 52 | |
| Semi-supervised classification | ADNI CN vs. AD (90% test) | Accuracy79.1 | 40 | |
| HC vs. MCI classification | ADNI (five-fold cross-validation) | AUC90.48 | 39 | |
| Brain disorder classification | ADNI (Five-fold cross-validation) | Accuracy93.2 | 38 | |
| User-based De-identification Matching | ADNI | Accuracy100 | 38 | |
| Age prediction | ADNI | MAE3.743 | 34 | |
| MMSE prediction | ADNI | MAE1.8 | 34 | |
| Diagnostic group separation analysis of hippocampal subfield volumes | ADNI3 cohort | Kruskal-Wallis H Statistic98.39 | 28 | |
| Classification | ADNI CN vs AD (test) | Accuracy81.17 | 28 | |
| AD diagnosis | ADNI (test) | Bacc83.6 | 28 | |
| Regression | ADNI clinical tabular dataset | Average MSE0.167 | 27 | |
| MCI vs. AD classification | ADNI | Accuracy86.84 | 26 | |
| Brain Tissue Segmentation | ADNI (test) | Dice Coefficient (CSF)99 | 26 | |
| Unsupervised clustering | ADNI CN vs AD | Accuracy78.5 | 25 | |
| Alzheimer's Disease Classification | ADNI 137 (test) | Accuracy0.7139 | 23 | |
| Binary diagnostic classification (SCD vs. MCI) | ADNI | Accuracy73.12 | 22 | |
| Binary diagnostic classification (HC vs. SCD) | ADNI | Accuracy72.84 | 22 | |
| Semi-supervised classification | ADNI CN vs. MCI (10% train, 90% test) | Accuracy81.5 | 20 |
Showing 25 of 212 rows
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