2024
Development of Clinical NLP Systems
Xu H, Demner Fushman D. Development of Clinical NLP Systems. Cognitive Informatics In Biomedicine And Healthcare 2024, 301-324. DOI: 10.1007/978-3-031-55865-8_11.Peer-Reviewed Original Research
2016
A long journey to short abbreviations: developing an open-source framework for clinical abbreviation recognition and disambiguation (CARD)
Wu Y, Denny J, Rosenbloom S, Miller R, Giuse D, Wang L, Blanquicett C, Soysal E, Xu J, Xu H. A long journey to short abbreviations: developing an open-source framework for clinical abbreviation recognition and disambiguation (CARD). Journal Of The American Medical Informatics Association 2016, 24: e79-e86. PMID: 27539197, PMCID: PMC7651947, DOI: 10.1093/jamia/ocw109.Peer-Reviewed Original ResearchConceptsClinical NLP systemsOpen-source frameworkNLP systemsClinical corpusClinical abbreviationsClinic visit notesSense inventoryKnowledge Extraction SystemAbbreviation recognitionWord sense disambiguation methodDischarge summariesF1 scoreExternal corpusClinical narrativesSense disambiguation methodSystem capabilitiesVanderbilt University Medical CenterWrapperFrequent abbreviationsDisambiguation methodMetaMapAbbreviation identificationCardsVisit notesDisambiguation
2015
Ease of adoption of clinical natural language processing software: An evaluation of five systems
Zheng K, Vydiswaran V, Liu Y, Wang Y, Stubbs A, Uzuner Ö, Gururaj A, Bayer S, Aberdeen J, Rumshisky A, Pakhomov S, Liu H, Xu H. Ease of adoption of clinical natural language processing software: An evaluation of five systems. Journal Of Biomedical Informatics 2015, 58: s189-s196. PMID: 26210361, PMCID: PMC4974203, DOI: 10.1016/j.jbi.2015.07.008.Peer-Reviewed Original ResearchConceptsClinical NLP systemsNLP systemsNatural language processing softwareThird-party componentsUsability testing toolGroup of usersLanguage processing softwareEase of adoptionExpert evaluatorsSoftware distributionBiomedical softwareComputer scienceEnd usersUsability assessmentI2b2 challengeTesting toolsEvaluation showHuman evaluatorsSystem submissionsEase of useHealth informaticsProcessing softwareAdoption issuesUsersSpecial trackA Preliminary Study of Clinical Abbreviation Disambiguation in Real Time
Wu Y, Denny J, Rosenbloom S, Miller R, Giuse D, Song M, Xu H. A Preliminary Study of Clinical Abbreviation Disambiguation in Real Time. Applied Clinical Informatics 2015, 06: 364-374. PMID: 26171081, PMCID: PMC4493336, DOI: 10.4338/aci-2014-10-ra-0088.Peer-Reviewed Original ResearchConceptsElectronic health record systemsUser studyClinical documentation systemNatural language processing systemsClinical NLP systemsPreliminary user studyAbbreviation recognitionExtra time costLanguage processing systemWSD methodHealth record systemsDocumentation systemPrototype applicationWord sense disambiguation methodNLP systemsCorrect sensesNote generationPrototype systemClinical sentencesCost of timeClinical documentsDocument entryDisambiguation moduleSense disambiguation methodHealthcare records
2013
A prototype application for real-time recognition and disambiguation of clinical abbreviations
Wu Y, Denny J, Rosenbloom S, Miller R, Giuse D, Song M, Xu H. A prototype application for real-time recognition and disambiguation of clinical abbreviations. 2013, 7-8. DOI: 10.1145/2512089.2512096.Peer-Reviewed Original ResearchElectronic health record systemsPrototype applicationClinical documentation systemNatural language processing systemsClinical abbreviationsClinical NLP systemsReal-time recognitionLanguage processing systemAverage response timeHealth record systemsDocumentation systemResponse timeWord sense disambiguation methodNLP systemsNote generationPrototype systemClinical documentsSense disambiguation methodHealthcare recordsProcessing systemAbbreviation disambiguationCard systemDisambiguation methodAbbreviation recognitionSystem design
2012
Recognition of medication information from discharge summaries using ensembles of classifiers
Doan S, Collier N, Xu H, Duy P, Phuong T. Recognition of medication information from discharge summaries using ensembles of classifiers. BMC Medical Informatics And Decision Making 2012, 12: 36. PMID: 22564405, PMCID: PMC3502425, DOI: 10.1186/1472-6947-12-36.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceDecision Support TechniquesFemaleHumansInformation Storage and RetrievalInstitutional Management TeamsMaleMedication SystemsNatural Language ProcessingPatient DischargePattern Recognition, AutomatedPharmaceutical PreparationsReproducibility of ResultsSemanticsSoftware DesignSupport Vector MachineConceptsConditional Random FieldsNatural language processingClinical natural language processingSupport vector machineBest F-scoreEnsemble classifierF-scoreClinical textIndividual classifiersVoting methodMajority votingLocal support vector machineSupervised machine learning methodsClinical entity recognitionClinical NLP systemsDifferent voting strategiesEntity recognition systemRule-based systemEnsemble of classifiersMachine learning methodsRule-based methodI2b2 NLP challengeEntity recognitionRecognition systemNLP systems