Table 3 Predictive value of the final models: area under the curve and discrimination parameters of the models obtained by the three linear discriminant (LD) binary classifiers.
BD vs. CT | SZ vs. CT | BD vs. SZ | |
|---|---|---|---|
Single domain—immune blood | |||
General AUC | 0.73 | 0.71 | 0.75 |
Accuracy | 69.17% | 70.30% | 71.73% |
True positive rate (Sensitivity) | 72.31% | 71.48% | 79.10% |
True negative rate (Specificity) | 64.39% | 61.27% | 64.49% |
False positive rate (1—Specificity) | 35.61% | 38.73% | 35.51% |
False negative rate (1—Sensitivity) | 27.69% | 28.52% | 20.90% |
Single domain—cognition | |||
General AUC | 0.81 | 0.90 | 0.77 |
Accuracy | 75.35% | 87.06% | 72.14% |
True positive rate (Sensitivity) | 76.12% | 84.43% | 71.39% |
True negative rate (Specificity) | 71.19% | 81.14% | 71.27% |
False positive rate (1—Specificity) | 28.81% | 18.86% | 28.73% |
False negative rate (1—Sensitivity) | 23.88% | 15.53% | 28.61% |
Multi-domain—immune blood + cognition | |||
General AUC | 0.86 | 0.89 | 0.80 |
Accuracy | 79.73% | 86.18% | 76.43% |
True positive rate (Sensitivity) | 88.29% | 84.46% | 71.29% |
True negative rate (Specificity) | 71.11% | 81.39% | 73.33% |
False positive rate (1—Specificity) | 28.89% | 18.61% | 26.67% |
False negative rate (1—Sensitivity) | 11.71.% | 15.54% | 28.71% |
