Research Article
A Novel Metabolic Connectome Method to Predict Progression to Mild Cognitive Impairment
Table 5
The predictive performance of the different methods in MCI conversion study.
| Reference | Method | Conversion time (month) | sMCI () | pMCI () | Accuracy (%) | Sensitivity (%) | Specificity (%) | AUC |
| Young et al. | Gaussian process | 36 | 96 | 47 | 65.0 | 66.0 | 64.6 | 0.767 | Liu et al. | Independent component analysis and Cox model | 36 | 108 | 126 | 68.8 | 57.1 | 82.4 | 0.736 | Lange et al. | SPM -test | 36 | 77 | 31 | / | / | / | 0.832 | Kengo et al. | Logistic regression | 24 | 47 | 41 | 83 | 70 | 90 | / | Lu et al. | Deep neural network | 36 | 409 | 217 | 81.5 | 78.2 | 82.5 | / | Pagani et al. | Independent components analysis | 60 | 27 | 95 | 83.5 | 83.2 | 85.2 | 0.894 | Proposed | Metabolic CPM | 36 | 242 | 178 | 85.2 | 88.1 | 86.4 | 0.933 |
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