Pytorch Implementation for Multi-view Transfer Attention Network for Dementia Status Prediction
Results:(Training on ADNI-1 and testing on ADNI-2)
| Methods | CDRSB | ADAS11 | ADAS13 | MMSE | ||||
|---|---|---|---|---|---|---|---|---|
| CC | RMSE | CC | RMSE | CC | RMSE | CC | RMSE | |
| ROI | 0.303 | 2.343 | 0.374 | 8.136 | 0.397 | 11.616 | 0.361 | 3.111 |
| VBM | 0.567 | 2.014 | 0.523 | 7.609 | 0.531 | 10.875 | 0.469 | 2.970 |
| VIT-mean | 0.537 | 1.944 | 0.562 | 8.027 | 0.591 | 10.831 | 0.516 | 2.831 |
| VIT-cls | 0.568 | 1.885 | 0.564 | 7.116 | 0.584 | 9.718 | 0.516 | 2.603 |
| CNN | 0.539 | 1.671 | 0.584 | 5.921 | 0.600 | 8.252 | 0.512 | 2.521 |
| wiseDNN | 0.532 | 1.664 | 0.561 | 6.234 | 0.586 | 8.536 | 0.502 | 2.435 |
| MTAN | 0.583 | 1.586 | 0.602 | 5.509 | 0.636 | 7.812 | 0.580 | 2.353 |