Fig. 4 | Scientific Reports

Fig. 4

From: Interpretable machine learning model for predicting post-hepatectomy liver failure in hepatocellular carcinoma

Fig. 4

The calibration curve and decision curve analysis curve were used to evaluate the accuracy and clinical application value of the XGBoost model. (A) Calibration curve for the training cohort. (B) Calibration curve for the validation cohort. (C) Calibration curve of the test cohort. (D) DCA curve for the training cohort. (E) DCA curve for the validation cohort. (F) DCA curve for the prospective cohort. Note The all curve illustrated the benefit rates for all cases that received the intervention, while the none curve depicted the benefit rates for all cases that did not received any intervention. The pred curves represented the XGBoost model. DCA, decision curve analysis.

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