Fig. 1 | Scientific Reports

Fig. 1

From: Selective classification with machine learning uncertainty estimates improves ACS prediction: a retrospective study in the prehospital setting

Fig. 1

AUROC performance for three different methods (GBDT, HEAR16, HEART13) as we exclude more uncertain cases. Performance is computed with the non-excluded cases. Uncertainty is the predictive uncertainty from GBDT (Eq. 1). Highlighted is the mean and shaded is two standard deviations from 5-fold cross validation. For this experiment, GBDT uses less covariates than those in Table 1 to match the HEAR16 covariates. Traditional HEART13 requires troponin, in addition to the HEAR covariates. A troponin measurement is generally unavailable in the prehospital setting.

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