Additional Table 2.
Predictions acquired using six different models
| CTH-SVM | CTH-J48 | CTH-NB | HCV-SVM | HCV-J48 | HCV-NB | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AD | MCI | AD | MCI | AD | MCI | AD | MCI | AD | MCI | AD | MCI | |
| MCIc | 99% | 1% | 99% | 1% | 99% | 1% | 0 | 100% | 7% | 93% | 5% | 95% |
| ACC | 83% | 84% | 83% | 6% | 14% | 9% | ||||||
The data are presented as the percentage of MCIc that were correctly classified as AD vs. misclassifications of MCIc as MCI (Skolariki et al., 2020). AD: Alzheimer’s disease; ACC: accuracy; MCI: mild cognitive impairment; CTH: cortical thickness; J48: the C4.5 algorithm; MCIc: MCI converters; NB: Naive Bayes; SVM: support vector machine.