Three-class Alzheimer's diagnosis stage classification on Pooled neuroimaging datasets (five-fold CV)
95.13AccuracyMT-M3AD-C3
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| MT-M3AD-C3Pre-trained initialization=SimMIM2025.08 | 95.13 | 94.84 | 94.15 | 97.54 | 94.48 | |
| MT-M3AD-C9Pre-trained initialization=SimMIM2025.08 | 94.72 | 93.82 | 95.23 | 97.03 | 94.47 | |
| MCLNC2025.08 | 90.44 | 86.29 | 88.97 | 93.47 | 87.47 | |
| ViT2025.08 | 89.54 | 88.91 | 89.12 | 92.67 | 89.01 | |
| ResNet-502025.08 | 89.21 | 88.45 | 87.93 | 92.13 | 88.18 | |
| DenseNet2025.08 | 88.67 | 87.32 | 88.01 | 91.45 | 87.66 | |
| PDMML2025.08 | 80.8 | 81 | 81 | — | 81 | |
| Stacked DAE2025.08 | 78 | 78 | 77 | — | 78 | |
| MCAD2025.08 | 64.03 | 63.85 | — | 82 | 61.85 |