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Fig. 8 | BMC Anesthesiology

Fig. 8

From: Prediction model of in-hospital mortality in intensive care unit patients with cardiac arrest: a retrospective analysis of MIMIC -IV database based on machine learning

Fig. 8

A Decision curve analysis for LASSO model, XGBoost model, LR model and NEWS 2 model. The y-axis measures the net benefit. The red line represents the LASSO model. The green line represents the XGBoost model. The yellow line represents the LR model. The blue line represents the NEWS 2 model. The grey line represents the assumption that all patients die in the hospital. The black line represents the assumption that no patients die in the hospital. B The comparison of ROC curves for LASSO model, XGBoost model, LR model and NEWS 2 model. LASSO, least absolute shrinkage and selection operator; LR, logistic regression; NEWS 2, the national early warning score 2; ROC, receiver operating characteristic; XGBoost, extreme gradient boosting

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