Unrecognized Fibrosis Risk in MASLD: A Real-World Analysis and the Case for AI-Augmented Stratification

Significant gaps persist in MASLD fibrosis risk stratification and management, largely reflecting system-level coordination failures rather than access barriers. Artificial intelligence-driven workflows integrated into the electronic health record could automate steatosis detection, calculate FIB-4 scores, flag care gaps, and prompt risk-stratified referrals or reassessments, offering a scalable solution to standardize MASLD management and improve outcomes.