Table 2.
Parameters of the SVM models for DDA and MRM datasets.
| DDA Dataset |
||||||
|---|---|---|---|---|---|---|
| Training set |
Test set |
|||||
| ESI+ | specificity | sensitivity | accuracy | specificity | sensitivity | accuracy |
| mean | 1.000 | 1.000 | 1.000 | 0.999 | 0.998 | 0.999 |
| 95% CI down | 1.000 | 1.000 | 1.000 | 0.998 | 0.997 | 0.997 |
| 95% CI up | 1.000 | 1.000 | 1.000 | 1.000 | 0.999 | 1.000 |
| ESI- | specificity | sensitivity | accuracy | specificity | sensitivity | accuracy |
| mean | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
| 95% CI down | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
| 95% CI up | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
| MRM Dataset | ||||||
| Training cohort | Test cohort | Validation cohort | ||||
| Accuracy | 0.9467 | 0.9244 | 0.9641 | |||
| Specificity | 0.9534 | 0.9727 | 0.9859 | |||
| Sensitivity | 0.9403 | 0.8783 | 0.9288 | |||
| AUC of ROC | 0.9877 | 0.9869 | 0.9866 | |||