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Fig. 1 | Critical Care

Fig. 1

From: Emergency department triage prediction of clinical outcomes using machine learning models

Fig. 1

Prediction ability of the reference model and machine learning models for intensive care use and in-hospital mortality in the test set. a Receiver-operating-characteristics (ROC) curves. The corresponding values of the area under the receiver-operating-characteristics curve (AUC) for each model are presented in Table 2. b Decision curve analysis. X-axis indicates the threshold probability for critical care outcome and Y-axis indicates the net benefit. Compared to the reference model, the net benefit for all machine learning models was larger over the range of clinical threshold

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