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 publicationsESMO AI & Digital OncologyNovember 2025Survival prediction in advanced NSCLC (aNSCLC) amid evolving standards of care (SOC): Digital twin modeling incorporating LLM-extracted clinical contextEstevez M, Griffith S, Williams T, et al.Publication summaryPublicationsMachine learningESMO AI & Digital OncologyNovember 2025A pan-tumor and pan-country approach to LLM-based extraction of systemic therapies from the electronic health recordViani N, Groizard L, Harrison K, et al. Publication summaryPublicationsMachine learningTumor agnosticData managementESMO AI & Digital OncologyNovember 2025Structuring GDPR-compliant private networks to enable LLM-Extracted oncology data on pseudonymized patient EHR data in EuropeEllsworth L, Groizard L, Stefan F, et al.Publication summaryPublicationsData scienceMachine learning