Table IV.
Comparison of the no information model and machine learning algorithms as predictors of ciTBI in children with no clinical evidence of skull fractures and GCS scores of 14 or 15
| Models | GCS score of 14 |
GCS score of 15 |
||||||
|---|---|---|---|---|---|---|---|---|
| True negative | False negative | ciTBI rate | P value | True negative | False negative | ciTBI rate | P value | |
| No information | 392 | 26 | 0.062 | 1 | 13 492 | 65 | 0.00479 | 1 |
| Logistic regression | 389 | 26 | 0.063 | 1 | 13 492 | 65 | 0.00479 | 1 |
| Classification and regression tree | 389 | 26 | 0.063 | 1 | 13 492 | 65 | 0.00479 | 1 |
| Random forest | 389 | 26 | 0.063 | 1 | 13 492 | 65 | 0.00479 | 1 |
| Generalized boosted model | 392 | 26 | 0.062 | 1 | 13 492 | 65 | 0.00479 | 1 |