Machine learning-based models for advanced fibrosis in non-alcoholic steatohepatitis patients: A cohort study

Figure 4 The receiver operating characteristic of comparing Extreme Gradient Boosting models with another non-invasive diagnosis model. A: Training cohort; B Validation cohort. The receiver operating characteristic of the Extreme Gradient Boosting (XGBoost) model and XGBoost + liver stiffness measure model were much better than aspartate aminotransferase to platelet ratio index scores and Fibrosis-4 scores. APRI: Aspartate aminotransferase to platelet ratio index score; FIB-4: Fibrosis index based on the 4 factors; LSM: Liver stiffness measure; AUC: Area under the curve; XGBoost: Extreme Gradient Boosting.