Classification results of different algorithms on ADNI II dataset. The classification task is to classify HC and AD
| Inputs . | Methods . | Accuracy . | Sensitivity . | Specificity . |
|---|---|---|---|---|
| Static FCs | SVM (linear kernel) | 68.8% | 72.2% | 65.9% |
| Spectral GCN | 81.3% | 88.9% | 75.0% | |
| CNN | / | / | / | |
| Dynamic FCs | LSTM | 78.8% | 86.1% | 72.7% |
| DS-GCN | 83.8% | 80.6% | 86.4% |
| Inputs . | Methods . | Accuracy . | Sensitivity . | Specificity . |
|---|---|---|---|---|
| Static FCs | SVM (linear kernel) | 68.8% | 72.2% | 65.9% |
| Spectral GCN | 81.3% | 88.9% | 75.0% | |
| CNN | / | / | / | |
| Dynamic FCs | LSTM | 78.8% | 86.1% | 72.7% |
| DS-GCN | 83.8% | 80.6% | 86.4% |
Classification results of different algorithms on ADNI II dataset. The classification task is to classify HC and AD
| Inputs . | Methods . | Accuracy . | Sensitivity . | Specificity . |
|---|---|---|---|---|
| Static FCs | SVM (linear kernel) | 68.8% | 72.2% | 65.9% |
| Spectral GCN | 81.3% | 88.9% | 75.0% | |
| CNN | / | / | / | |
| Dynamic FCs | LSTM | 78.8% | 86.1% | 72.7% |
| DS-GCN | 83.8% | 80.6% | 86.4% |
| Inputs . | Methods . | Accuracy . | Sensitivity . | Specificity . |
|---|---|---|---|---|
| Static FCs | SVM (linear kernel) | 68.8% | 72.2% | 65.9% |
| Spectral GCN | 81.3% | 88.9% | 75.0% | |
| CNN | / | / | / | |
| Dynamic FCs | LSTM | 78.8% | 86.1% | 72.7% |
| DS-GCN | 83.8% | 80.6% | 86.4% |
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