# AI in Endohepatology

This narrative review is the first to synthesize the convergence of artificial intelligence and endohepatology into four functional pillars—intelligent hemodynamic assessment, virtual histology, precision tissue acquisition, and integrated risk stratification with therapeutic and decision support—and proposes a three-tier readiness framework to separate demonstrated capabilities from extrapolated and conceptual applications, concluding that the field is still very early-stage but that AI has strong potential to turn endohepatology into a single machine-driven diagnostic and therapeutic platform provided standardized datasets, prospective validation, and clear regulatory and governance standards are in place.

This narrative review is the first to synthesize the convergence of artificial intelligence and endohepatology into four functional pillars—intelligent hemodynamic assessment, virtual histology, precision tissue acquisition, and integrated risk stratification with therapeutic and decision support—and proposes a three-tier readiness framework to separate demonstrated capabilities from extrapolated and conceptual applications, concluding that the field is still very early-stage but that AI has strong potential to turn endohepatology into a single machine-driven diagnostic and therapeutic platform provided standardized datasets, prospective validation, and clear regulatory and governance standards are in place.