2013
Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features
Tang B, Cao H, Wu Y, Jiang M, Xu H. Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features. BMC Medical Informatics And Decision Making 2013, 13: s1. PMID: 23566040, PMCID: PMC3618243, DOI: 10.1186/1472-6947-13-s1-s1.Peer-Reviewed Original ResearchConceptsStructural support vector machineWord representation featuresClinical NER tasksConditional Random FieldsSupport vector machinePerformance of MLClinical NER systemMachine learningRepresentation featuresNER systemNER taskVector machineEntity recognitionNatural language processing researchSequential labeling algorithmClinical entity recognitionLarge margin theoryClinical text processingLanguage processing researchPerformance of CRFsHighest F-measureClinical NLP researchI2b2 NLP challengeSame feature setsBetter performance
2011
Modeling drug exposure data in electronic medical records: an application to warfarin.
Liu M, Jiang M, Kawai V, Stein C, Roden D, Denny J, Xu H. Modeling drug exposure data in electronic medical records: an application to warfarin. AMIA Annual Symposium Proceedings 2011, 2011: 815-23. PMID: 22195139, PMCID: PMC3243123.Peer-Reviewed Original ResearchMeSH KeywordsArtificial IntelligenceElectronic Health RecordsHospitalizationHumansMedical Records Systems, ComputerizedModels, TheoreticalNatural Language ProcessingWarfarinConceptsNatural language processingMachine learning technologiesElectronic medical recordsDrug exposure informationLearning technologyLanguage processingTemporal informationInformatics frameworkClinical narrativesDrug mentionsMedical recordsDrug exposure dataFrameworkReceiver operator characteristic curveDrug exposure historyInformationDrug-related researchWarfarin exposureDrug regimensHospital admissionDrug exposureAccurate modelingDrug informationExposure informationExposure data
2008
Methods for building sense inventories of abbreviations in clinical notes.
Xu H, Stetson P, Friedman C. Methods for building sense inventories of abbreviations in clinical notes. AMIA Annual Symposium Proceedings 2008, 2008: 819. PMID: 18999007, PMCID: PMC2656023.Peer-Reviewed Original Research
2007
Automated Acquisition of Disease–Drug Knowledge from Biomedical and Clinical Documents: An Initial Study
Chen E, Hripcsak G, Xu H, Markatou M, Friedman C. Automated Acquisition of Disease–Drug Knowledge from Biomedical and Clinical Documents: An Initial Study. Journal Of The American Medical Informatics Association 2007, 15: 87-98. PMID: 17947625, PMCID: PMC2274872, DOI: 10.1197/jamia.m2401.Peer-Reviewed Original Research