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Fig. 5 | European Journal of Medical Research

Fig. 5

From: The prediction of in-hospital mortality in chronic kidney disease patients with coronary artery disease using machine learning models

Fig. 5

External validation for the GBDT model in the eICU-CRD dataset. A DCA curve of the GBDT model in external validation. B calibration curve of the GBDT model in external validation. C ROC of the GBDT model in external validation. D P-R curves of the GBDT models in external validation. DCA showed the GBDT model had some net benefit compared with the “treat-none” or “treat-all” strategies with a certain degree of clinical utility. The AUC (0.865) and AP (0.672) results demonstrated the GBDT model had good predictive values in external validation. DCA decision curve analysis, ROC Receiver Operating Characteristic, P-R curve precision/recall curve, GBDT Gradient Boosting Decision Tree Machine, eICU-CRD Telehealth Intensive Care Unit Collaborative Research Database

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