Retrospective cohort study of Helicobacter pylori infection and risk stratification using 6-year UBT data

This study underscores the interplay between chronic <i>H. pylori</i> infection and metabolic dysfunction, offering new perspectives on risk prediction using machine learning. The XGBoost model demonstrated reliable performance in stratifying infection risk based on accessible clinical markers. Its integration into routine screening protocols could enhance early detection and personalized intervention strategies. Further studies should validate these findings across broader populations and incorporate additional risk factors.