To evaluate the feasibility of using large language models (LLMs) to automate ground truth label extraction from radiology reports, enabling scalable assessment and monitoring of radiology artificial intelligence (AI) tools. The framework is tested by validating AI model performance on a newly installed photon-counting CT (PCCT) scanner.

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