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A new system called CDR-Agent, based on large language models, has been developed to assist emergency department clinicians by autonomously identifying and applying appropriate Clinical Decision Rules (CDRs) from unstructured clinical notes, thereby reducing cognitive load and improving decision accuracy. Validated on synthetic and real datasets, CDR-Agent significantly outperforms baseline models in CDR selection accuracy and helps make more efficient and cautious imaging decisions, minimizing unnecessary interventions.