2023
An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C)
Liu S, Wen A, Wang L, He H, Fu S, Miller R, Williams A, Harris D, Kavuluru R, Liu M, Abu-el-Rub N, Schutte D, Zhang R, Rouhizadeh M, Osborne J, He Y, Topaloglu U, Hong S, Saltz J, Schaffter T, Pfaff E, Chute C, Duong T, Haendel M, Fuentes R, Szolovits P, Xu H, Liu H. An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C). Journal Of The American Medical Informatics Association 2023, 30: 2036-2040. PMID: 37555837, PMCID: PMC10654844, DOI: 10.1093/jamia/ocad134.Peer-Reviewed Original ResearchConceptsNatural language processingNLP modelsClinical natural language processingNatural language processing frameworkEHR-based clinical researchMulti-site settingSymptom extractionProcessing frameworkNLP frameworkLanguage processingNLP solutionMulti-site dataAlgorithm robustnessMethodology advancementsResearch communityTranslational research communityNational COVID Cohort CollaborativeCase demonstrationProcess heterogeneityFrameworkAnnotationCOVID cohortRepresenting and utilizing clinical textual data for real world studies: An OHDSI approach
Keloth V, Banda J, Gurley M, Heider P, Kennedy G, Liu H, Liu F, Miller T, Natarajan K, V Patterson O, Peng Y, Raja K, Reeves R, Rouhizadeh M, Shi J, Wang X, Wang Y, Wei W, Williams A, Zhang R, Belenkaya R, Reich C, Blacketer C, Ryan P, Hripcsak G, Elhadad N, Xu H. Representing and utilizing clinical textual data for real world studies: An OHDSI approach. Journal Of Biomedical Informatics 2023, 142: 104343. PMID: 36935011, PMCID: PMC10428170, DOI: 10.1016/j.jbi.2023.104343.Peer-Reviewed Original ResearchConceptsNatural language processingCommon data modelTextual dataNLP solutionObservational Health Data SciencesOMOP Common Data ModelSpecific use casesObservational Medical Outcomes Partnership Common Data ModelHealth Data SciencesRepresentation of informationUse casesElectronic health recordsReal-world evidence generationData scienceClinical textData modelClinical notesLanguage processingHealth recordsLoad dataClinical documentationCurrent applicationsInformationWorkflowEvidence generation
2019
Developing Customizable Cancer Information Extraction Modules for Pathology Reports Using CLAMP
Soysal E, Warner J, Wang J, Jiang M, Harvey K, Jain S, Dong X, Song H, Siddhanamatha H, Wang L, Dai Q, Chen Q, Du X, Tao C, Yang P, Denny J, Liu H, Xu H. Developing Customizable Cancer Information Extraction Modules for Pathology Reports Using CLAMP. Studies In Health Technology And Informatics 2019, 264: 1041-1045. PMID: 31438083, PMCID: PMC7359882, DOI: 10.3233/shti190383.Peer-Reviewed Original ResearchConceptsElectronic health recordsNLP solutionNatural language processing technologyInformation extraction moduleLanguage processing technologyInformation extraction tasksUser-friendly interfaceBest F-measureInformation extractionExtraction moduleExtraction taskCustomizable modulesNLP systemsF-measureAcademic useHealth recordsComparable performanceProcessing technologyVanderbilt University Medical CenterModuleDiverse typesInformationNLPSubstantial effortSystem
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