2018
Leveraging existing corpora for de-identification of psychiatric notes using domain adaptation.
Lee H, Zhang Y, Roberts K, Xu H. Leveraging existing corpora for de-identification of psychiatric notes using domain adaptation. AMIA Annual Symposium Proceedings 2018, 2017: 1070-1079. PMID: 29854175, PMCID: PMC5977650.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
2012
Extracting semantic lexicons from discharge summaries using machine learning and the C-Value method.
Jiang M, Denny J, Tang B, Cao H, Xu H. Extracting semantic lexicons from discharge summaries using machine learning and the C-Value method. AMIA Annual Symposium Proceedings 2012, 2012: 409-16. PMID: 23304311, PMCID: PMC3540581.Peer-Reviewed Original Research
2011
Detecting abbreviations in discharge summaries using machine learning methods.
Wu Y, Rosenbloom S, Denny J, Miller R, Mani S, Giuse D, Xu H. Detecting abbreviations in discharge summaries using machine learning methods. AMIA Annual Symposium Proceedings 2011, 2011: 1541-9. PMID: 22195219, PMCID: PMC3243185.Peer-Reviewed Original ResearchConceptsNatural language processingMachine learning methodsHighest F-measureF-measureClinical natural language processingLexical resourcesClinical abbreviationsTraining setPre-defined featuresRandom forest classifierDomain expertsML algorithmsML classifiersLanguage processingVoting schemeLearning methodsDischarge summariesForest classifierTest setClassifierCorpus-based methodSetResourcesAlgorithmAbbreviations
2010
Recognizing Medication related Entities in Hospital Discharge Summaries using Support Vector Machine.
Doan S, Xu H. Recognizing Medication related Entities in Hospital Discharge Summaries using Support Vector Machine. Proceedings - International Conference On Computational Linguistics 2010, 2010: 259-266. PMID: 26848286, PMCID: PMC4736747.Peer-Reviewed Original ResearchSupport vector machineHospital discharge summariesConditional Random FieldsDischarge summariesMedication namesRelated entitiesClinical textVector machineType of medicationNamed Entity Recognition (NER) taskEntity recognition taskRule-based systemBest F-scoreI2b2 NLP challengeTypes of featuresF-scoreI2b2 challengeNLP challengeNER systemSemantic featuresRecognition taskMachineData setsRandom fieldsBetter performanceMedEx: a medication information extraction system for clinical narratives
Xu H, Stenner S, Doan S, Johnson K, Waitman L, Denny J. MedEx: a medication information extraction system for clinical narratives. Journal Of The American Medical Informatics Association 2010, 17: 19-24. PMID: 20064797, PMCID: PMC2995636, DOI: 10.1197/jamia.m3378.Peer-Reviewed Original ResearchConceptsClinic visit notesVisit notesMedication informationClinical notesDischarge summariesElectronic medical record dataMedical record dataElectronic medical recordsMedication dataMedical recordsClinical dataClinical researchRecord dataHealthcare safetyDrug namesMedexF-measureClinical narrativesNatural language processing systemsInformation extraction system