GPT and diabetes mellitus: Katarzyna and colleagues, in their investigation of 1,735 diabetic patients, utilized eight clinical indices—age, BMI, type of diabetes, ALT, AST, hyperuricemia, platelet count, and metformin treatment—combined with a machine-learning approach, successfully developed an identification model for MASLD (AUC = 0.84) (28).