SEETrials: Leveraging large language models for safety and efficacy extraction in oncology clinical trials
Lee K, Paek H, Huang L, Hilton C, Datta S, Higashi J, Ofoegbu N, Wang J, Rubinstein S, Cowan A, Kwok M, Warner J, Xu H, Wang X. SEETrials: Leveraging large language models for safety and efficacy extraction in oncology clinical trials. Informatics In Medicine Unlocked 2024, 50: 101589. PMID: 39493413, PMCID: PMC11530223, DOI: 10.1016/j.imu.2024.101589.Peer-Reviewed Original ResearchAntibody-drug conjugatesOverall response rateMultiple myelomaF1 scoreCAR-TComplete responseBispecific antibodiesComparative performance analysisClinical trial studyClinical trial outcomesLanguage modelAccurate data extractionTherapy subgroupFine granularityOncology clinical trialsAdverse eventsClinical decision-makingPerformance analysisClinical trialsInnovative therapiesDiverse therapiesClinical trial abstractsCancer domainData elementsTherapyUnveiling consistency: A large-scale analysis of conference proceedings and subsequent publications in oncology clinical trials using large language models.
Lee K, Paek H, Huang L, Datta S, Annan A, Ofoegbu N, Higashi M, Hilton C, Rubinstein S, Cowan A, Kwok M, Warner J, Xu H, Wang X. Unveiling consistency: A large-scale analysis of conference proceedings and subsequent publications in oncology clinical trials using large language models. Journal Of Clinical Oncology 2024, 42: 7568-7568. DOI: 10.1200/jco.2024.42.16_suppl.7568.Peer-Reviewed Original ResearchAmerican Society of Clinical Oncology conferencesConference abstractsOncology clinical trialsStudies due to variationsEfficacy outcomesP-valueTwo-proportion z-testClinical trialsMinimal residual disease negativityLung cancer studiesPublished articlesTrial abstractsGood partial responseCohort sizeCytokine release syndromeOutcome valuesFollow-up timeOverall response rateTrial findingsClinical trial findingsTime pointsCancer studiesClinical decisionsDiverse cancer typesComplete response