Fig. 2

Screening of characteristic variables. a Six variables with non-zero coefficients were selected based on the optimal value of the parameter lambda. b After validating the optimal lambda value, the relationship between partial likelihood deviance and log (lambda) was plotted. The dashed vertical line represents the 1 − SE standard. c The orange solid point indicates that the coefficient of the variable is zero; the blue solid point indicates that the coefficient of the characteristic variable is not zero. d Based on the feature recursive elimination method, the RF model was used for feature extraction. Overall, 15 important variables were retained. e Ranking of feature importance of RF after tenfold cross-validation. RF, random forest, BMI, body mass index; TG, triglyceride level; ALT, alanine transaminase level; TC, total cholesterol; UA, uric acid level; HGB, haemoglobin; LDL, low-density lipoprotein level; AST, aspartate aminotransferase level; RBC, red blood cell count; LYMPH, lymphocyte count; DBP, diastolic blood pressure; GLU,; NEUT, neutrophil count; CRE, creatinine level; SBP, systolic blood pressure; PLT, platelet count; ALB, albumin level; AFP, alpha-fetoprotein level; TB, total bilirubin