Natural language processing-based detection of transgender and gender non-conforming patients in electronic health record-derived data Published May 2021 Citation Hooley, IJ, Maignan, K, Ngai, D, Ackerman, B. . ISPOR Annual Meeting. . https://www.ispor.org/heor-resources/presentations-database/presentation/intl2021-3338/109635 Authors:Hooley, IJ, Maignan, K, Ngai, D, Ackerman, B Sources:ISPOR Annual Meeting Share Posted inPublicationsMachine learningHealth equity More publicationsAACR Special Conference in Cancer Research: Artificial Intelligence and Machine LearningJuly 2025Using large language models for scalable extraction of real-world progression events across multiple cancer typesCohen A, Krismer K, Magee K, et al. Real-world evidencePublication summaryPublicationsData scienceMachine learningArtificial intelligenceAACR Special Conference in Cancer Research: Artificial Intelligence and Machine LearningJuly 2025Fairness by design: End-to-end bias evaluation for LLM-generated dataEstevez M, Mbah O, Sheikh A, et al.Publication summaryPublicationsData scienceHealth equityBreast cancerArtificial intelligencearXivJune 2025Ensuring reliability of curated EHR-derived data: The Validation of Accuracy for LLM/ML-Extracted Information and Data (VALID) FrameworkEstevez M, Singh N, Dyson L, et al. Publication summaryPublicationsMachine learningQuality improvementQuality reporting