Foundation models for X-ray interpretation: a narrative review of current techniques and future perspectives in diagnostic imaging

Abstract

CXR-FMs offer a path toward more generalizable and data-efficient diagnostic AI. However, successful clinical translation is contingent upon coordinated advances across all four pillars of the proposed framework, moving beyond architectural scaling to prioritize data diversity, robustness auditing, and seamless workflow integration. This taxonomy provides researchers and clinicians with an actionable framework to develop and evaluate models whose impact will be determined by demonstrated fairness, reliability, and utility in diverse clinical environments.

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