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 publicationsISPORApril 2026From real-world data (RWD) to digital twins: building models for patient-level counterfactual prediction in oncologyGriffith S, Manfredonia J, Ricottone M, et al.Publication summaryPublicationsMachine learningNon-small cell lung cancerArtificial intelligenceISPORApril 2026Assessing quality of a LLM-derived prostate cancer (PC) real-world dataset: an application of the validation of accuracy for LLM/ML-extracted information and data (VALID) frameworkWard PJ, Qian Y, Hankinson EA, Dolor A, Estevez M, et al.Publication summaryPublicationsMachine learningProstate cancerArtificial intelligenceISPORApril 2026Customization of a large language model approach to capture PSA and imaging derived real-world progression events in prostate cancerMagee K, Ward P, Chen W, Hankinson E, Dolor A, et al.Publication summaryPublicationsMachine learningProstate cancerArtificial intelligence