Figure 2 | Scientific Reports

Figure 2

From: Predicting sepsis onset using a machine learned causal probabilistic network algorithm based on electronic health records data

Figure 2

The discriminative performance of the algorithms in the validation set. The left panel shows a receiver operating characteristic curve, and the right panel shows a precision recall curve for the prediction of sepsis within 48 h using SepsisFinder (blue line), the NEWS2 (green line) and the GBDT model (yellow line). Operating alarm thresholds corresponding to NEWS2 equal to 5 and 7 points have been marked for both scores. For SepsisFinder and GBDT, an additional alarm threshold corresponding to approximately 85% sensitivity has been marked. The blue shaded area illustrates the suggested clinically applicable region, and the grey shaded area illustrates the suggested clinically inapplicable region (specificity < 90% and precision < 15%) of model performance. SepsisFinder (SF), Area Under Receiver Operating Characteristic curve (AUC), Area Under Precision Recall curve (APR), National Early Warning Score 2 (NEWS2), and gradient-boosting decision tree (GBDT).

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