2024
Mapping Clinical Documents to the Logical Observation Identifiers, Names and Codes (LOINC) Document Ontology using Electronic Health Record Systems Structured Metadata.
Khan H, Mosa A, Paka V, Rana M, Mandhadi V, Islam S, Xu H, McClay J, Sarker S, Rao P, Waitman L. Mapping Clinical Documents to the Logical Observation Identifiers, Names and Codes (LOINC) Document Ontology using Electronic Health Record Systems Structured Metadata. AMIA Annual Symposium Proceedings 2024, 2023: 1017-1026. PMID: 38222329, PMCID: PMC10785913.Peer-Reviewed Original ResearchMeSH KeywordsDocumentationElectronic Health RecordsHumansLogical Observation Identifiers Names and CodesMetadataConceptsDocument ontologyElectronic health recordsBag-of-words approachNatural language processing techniquesFree-text documentsLanguage processing techniquesClinical documentationLogical Observation IdentifiersText documentsStructured metadataWords approachComputational scalabilityMetadataHealth recordsEHR documentationElectronic health record fieldsProcessing techniquesOntologyDocumentsAutomated pipelineNLPScalabilityClinical careFrameworkLOINC
2022
Assess the documentation of cognitive tests and biomarkers in electronic health records via natural language processing for Alzheimer’s disease and related dementias
Chen Z, Zhang H, Yang X, Wu S, He X, Xu J, Guo J, Prosperi M, Wang F, Xu H, Chen Y, Hu H, DeKosky S, Farrer M, Guo Y, Wu Y, Bian J. Assess the documentation of cognitive tests and biomarkers in electronic health records via natural language processing for Alzheimer’s disease and related dementias. International Journal Of Medical Informatics 2022, 170: 104973. PMID: 36577203, PMCID: PMC11325083, DOI: 10.1016/j.ijmedinf.2022.104973.Peer-Reviewed Original ResearchMeSH KeywordsAlzheimer DiseaseBiomarkersDocumentationElectronic Health RecordsHumansNatural Language ProcessingConceptsElectronic health recordsPatients' electronic health recordsCognitive testsCognitive test scoresFlorida health systemSeverity categoriesHealth recordsAD-related dementiaAD/ADRD researchAD/ADRDPatient levelAlzheimer's diseaseClinical narrativesHealth systemBiomarkersDifferent severityDiseaseSeverityPatientsADRD researchStandardized approachDementiaTest scoresPopulation characteristicsScores
2018
Psychiatric stressor recognition from clinical notes to reveal association with suicide
Zhang Y, Zhang O, Li R, Flores A, Selek S, Zhang X, Xu H. Psychiatric stressor recognition from clinical notes to reveal association with suicide. Health Informatics Journal 2018, 25: 1846-1862. PMID: 30328378, DOI: 10.1177/1460458218796598.Peer-Reviewed Original ResearchConceptsElectronic health recordsSuicidal behaviorHealth recordsSuicide ideation/attemptsTremendous economic burdenPsychiatric stressorsSuicide risk factorsRisk factorsEconomic burdenPsychiatric stressClinical notesLarge-scale studiesPsychiatric notesSuicideAssociationSignificant stressorsStressorsPrior studiesPercentPrevious studiesStudyIdentifying direct temporal relations between time and events from clinical notes
Lee H, Zhang Y, Jiang M, Xu J, Tao C, Xu H. Identifying direct temporal relations between time and events from clinical notes. BMC Medical Informatics And Decision Making 2018, 18: 49. PMID: 30066643, PMCID: PMC6069692, DOI: 10.1186/s12911-018-0627-5.Peer-Reviewed Original Research
2015
A 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 ResearchMeSH KeywordsAbbreviations as TopicDocumentationHealth PersonnelNatural Language ProcessingTime FactorsUser-Computer InterfaceConceptsElectronic 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
Analyzing differences between chinese and english clinical text: a cross-institution comparison of discharge summaries in two languages.
Wu Y, Lei J, Wei W, Tang B, Denny J, Rosenbloom S, Miller R, Giuse D, Zheng K, Xu H. Analyzing differences between chinese and english clinical text: a cross-institution comparison of discharge summaries in two languages. 2013, 192: 662-6. PMID: 23920639, PMCID: PMC4957806.Peer-Reviewed Original ResearchConceptsNatural language processing toolsEnglish clinical textClinical textLanguage processing toolsChinese clinical textCultural differencesMajor clinical componentsTextWestern institutionsInpatient discharge summariesCross-country collaborationDocument levelProcessing toolsClinical documentsLanguageUS institutionsUsesUnprecedented amountValuable insightsInstitutionsDocumentsChinaWorldwide adoptionEMR dataCollaboration
2011
Data from clinical notes: a perspective on the tension between structure and flexible documentation
Rosenbloom S, Denny J, Xu H, Lorenzi N, Stead W, Johnson K. Data from clinical notes: a perspective on the tension between structure and flexible documentation. Journal Of The American Medical Informatics Association 2011, 18: 181-186. PMID: 21233086, PMCID: PMC3116264, DOI: 10.1136/jamia.2010.007237.Peer-Reviewed Original ResearchConceptsReusable dataElectronic health record system adoptionStructured documentationComputer-based documentation systemsClinical notesClinical documentationStructured dataText processingSystem adoptionRecord systemSuch systemsDocumentation systemWorkflowContent needsProvidersUsabilityDocumentationExpressivitySystemHealthcare providersPatient careDataProcessingMajor goalAdoption