Machine learning-based prediction models for liver-related events in patients with hepatitis B-related cirrhosis and clinically significant portal hypertension

Figure 2 Feature selection. A: Curve showing the change in variable coefficients for different λ values in least absolute shrinkage and selection operator (LASSO) regression; B: Curve showing the relationship between partial likelihood deviation and log(λ); C: Feature importance ranking calculated by the random forest (RF) algorithm; D: Feature importance ranking evaluated by the support vector machine (SVM) algorithm; E: Intersection Venn diagram of features screened by LASSO, RF, and SVM. LSPS: Liver stiffness-spleen diameter-to-platelet ratio score; LPR: Liver stiffness measurement-to-platelet ratio; ALB: Albumin; LAR: Liver stiffness measurement-to-albumin ratio; LSM: Liver stiffness measurement; PLT: Platelet; HB: Hemoglobin; AST: Aspartate aminotransferase; GGT: Gamma-glutamyltransferase; TB: Total bilirubin; ALP: Alkaline phosphatase; INR: International normalized ratio; WBC: White blood cell; PT: Prothrombin time; DB: Direct bilirubin; ALT: Alanine aminotransferase; A/G: Albumin/globulin ratio; LASSO: Least absolute shrinkage and selection operator.