Table 3.
Performance of machine learning model for predicting PE.
| Features | Hospital A | Hospital B |
|---|---|---|
| WC + D-dimer | WC + D-dimer | |
| AUROC | 0.736 (0.624–0.838) | 0.669 (0.557–0.767) |
| Accuracy | 0.433 (0.333–0.533) | 0.345 (0.226–0.424) |
| Sensitivity | 1.000 (1.000–1.000) | 0.976 (0.921-1.000) |
| NPV | 1.000 (1.000–1.000) | 0.889 (0.625-1.000) |
| Specificity | 0.136 (0.053–0.231) | 0.082 (0.030–0.136) |
| PPV | 0.378 (0.275–0.482) | 0.308 (0.231–0.388) |
PE pulmonary embolism, WC components of Wells score, AUROC area under receiver operating curve, NPV negative predictive value, PPV positive predictive value.