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Model of 10 ensembles of random forest classifiers. Classification performance is reported for external testing in terms of accuracy, sensitivity, specificity, PPV and NPV
| External testing | Random forest (majority vote—38.9% threshold) | Radiologist |
|---|---|---|
| Accuracy (%) | 53 (19/36) | 64 (23/36) |
| Sensitivity (%) | 92 (11/12) | 88 (10/12) |
| Specificity (%) | 33 (8/24) | 54 (13/24) |
| PPV (%) | 41 (11/27) | 48 (10/21) |
| NPV (%) | 89 (8/9) | 87 (13/15) |
p-value = 0.474 (machine learning vs. radiologist)
