Table 6 A list of previous models that train a classifier mainly using MCI samples.
From: Predicting Alzheimer’s disease progression using multi-modal deep learning approach
Method | Subjects (MCI-C/MCI-NC) | Data source | ACC | SEN | SPE |
|---|---|---|---|---|---|
SVM7 | 43/48 | MRI, PET, CSF | 0.73 | 0.68 | 0.73 |
SVM8 | 43/56 | MRI, FDG-PET, CSF | 0.79 | 0.84 | 0.72 |
SVM9 | 35/50 | MRI, PET, cognitive score | 0.78 | 0.79 | 0.78 |
Gaussian process39 | 47/96 | MRI, PET, CSF, APOE genotype | 0.68 | 0.90 | 0.52 |
Hierarchical ensemble25 | 70/61 | MRI | 0.79 | 0.86 | 0.78 |
Deep neural network27 | 235/409 | MRI, PET | 0.82 | 0.79 | 0.83 |
Proposed | 134/561 | Cognitive score, MRI, CSF biomarker, demographic data | 0.81 | 0.84 | 0.80 |
