2023
AutoCriteria: a generalizable clinical trial eligibility criteria extraction system powered by large language models
Datta S, Lee K, Paek H, Manion F, Ofoegbu N, Du J, Li Y, Huang L, Wang J, Lin B, Xu H, Wang X. AutoCriteria: a generalizable clinical trial eligibility criteria extraction system powered by large language models. Journal Of The American Medical Informatics Association 2023, 31: 375-385. PMID: 37952206, PMCID: PMC10797270, DOI: 10.1093/jamia/ocad218.Peer-Reviewed Original ResearchConceptsLanguage modelInformation extraction systemOverall F1 scoreCriteria informationF1 scoreManual annotationScalable solutionContextual informationComplex scenariosContextual attributesExtraction systemReal-world settingsSystem evaluationModeling capabilitiesClinical trial protocol documentsInformationProtocol documents
2012
A study of transportability of an existing smoking status detection module across institutions.
Liu M, Shah A, Jiang M, Peterson N, Dai Q, Aldrich M, Chen Q, Bowton E, Liu H, Denny J, Xu H. A study of transportability of an existing smoking status detection module across institutions. AMIA Annual Symposium Proceedings 2012, 2012: 577-86. PMID: 23304330, PMCID: PMC3540509.Peer-Reviewed Original ResearchConceptsDetection moduleNatural language processing systemsKnowledge Extraction SystemEMR dataRule-based classifierClinical Text AnalysisHighest F-measureLanguage processing systemElectronic medical recordsF-measureLevels of classificationProcessing systemSpecific tasksText analysisClassifierDesirable performanceModuleModest effortExtraction systemCTAKESSmoking moduleMachineSystemTaskClassification