Development and Internal Validation of an Interpretable Machine Learning Screening Model for MAFLD–Diabetes Mellitus Comorbidity: A Cross-Sectional NHANES Study
Background: The rising global prevalence and bidirectional relationship between metabolic-associated fatty liver disease (MAFLD) and diabetes mellitus (DM) significantly exacerbate adverse target-organ outcomes. Despite this, non-invasive screening frameworks remain lacking. This study aims to bridge this gap by develo...