Liver stiffness-platelet ratio index and machine learning models for the noninvasive diagnosis of significant fibrosis in chronic hepatitis B

Figure 6 Proposed clinical workflow for liver stiffness-platelet ratio index-based triage of significant fibrosis in treatment-naïve chronic hepatitis B. Patients are stratified into rule-out, indeterminate, and rule-in zones using lower and upper liver stiffness-platelet ratio index thresholds; complex machine learning/deep learning models may provide incremental accuracy in selected settings. aMAP: Age-male-alkaline phosphatase-platelets risk score; APAG: Aspartate aminotransferase to platelet and age-gender model; APRI: Aspartate aminotransferase to platelet ratio index; FIB-4: Fibrosis-4; GPR: Gamma-glutamyl transpeptidase to platelet ratio; KAN: Kolmogorov-Arnold Network; LPRI: Liver stiffness-platelet ratio index; NIT: Noninvasive test; PF: Random forest; S Index: S-Index; SVM: Support vector machine.