<ul><li>Large language models (LLMs) are being utilized to extract clinical data from electronic health records (EHRs) in oncology, improving scalability and efficiency.</li><li>A new framework, VALID, addresses challenges in ensuring reliability, accuracy, and fairness of LLM-extracted data for research, regulatory, and clinical applications in oncology.</li><li>VALID framework includes performance benchmarking against human experts, verification checks for consistency, and bias assessment across demographic subgroups.</li><li>This framework aims to enhance industry standards and support the trustworthy use of AI-powered evidence generation in oncology research and practice.</li></ul>

Ensuring Reliability of Curated EHR-Derived Data: The Validation of Accuracy for LLM/ML-Extracted Information and Data (VALID) Framework

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