Fig. 5 | Scientific Reports

Fig. 5

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

Fig. 5

The prediction accuracy of the XGBoost model and conventional models for post-hepatectomy liver failure was compared. Note MELD, the model for end-stage liver disease; ALBI, albumin-bilirubin score; ICG R15, indocyanine green retention rate at 15 min; APRI, aspartate aminotransferase to platelet ratio index; FIB-4, fibrosis-4 index; XGB, eXtreme Gradient Boosting.

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