2020
Learning from local to global: An efficient distributed algorithm for modeling time-to-event data
Duan R, Luo C, Schuemie M, Tong J, Liang C, Chang H, Boland M, Bian J, Xu H, Holmes J, Forrest C, Morton S, Berlin J, Moore J, Mahoney K, Chen Y. Learning from local to global: An efficient distributed algorithm for modeling time-to-event data. Journal Of The American Medical Informatics Association 2020, 27: 1028-1036. PMID: 32626900, PMCID: PMC7647322, DOI: 10.1093/jamia/ocaa044.Peer-Reviewed Original Research
2019
Time-sensitive clinical concept embeddings learned from large electronic health records
Xiang Y, Xu J, Si Y, Li Z, Rasmy L, Zhou Y, Tiryaki F, Li F, Zhang Y, Wu Y, Jiang X, Zheng W, Zhi D, Tao C, Xu H. Time-sensitive clinical concept embeddings learned from large electronic health records. BMC Medical Informatics And Decision Making 2019, 19: 58. PMID: 30961579, PMCID: PMC6454598, DOI: 10.1186/s12911-019-0766-3.Peer-Reviewed Original ResearchConceptsConcept similarity measurePositive pointwise mutual informationConcept embeddingsSimilarity measurePredictive modeling tasksLarge electronic health recordTime-sensitive informationPointwise mutual informationImportant research areaDeep learningElectronic health recordsMedical domainLarge electronic health record databaseWord2vec embeddingsTemporal dependenciesLearning methodsFastText algorithmModeling tasksResultsOur experimentsExtrinsic evaluationIntrinsic evaluationMutual informationHealth recordsDistributional representationsEmbeddingTemporal indexing of medical entity in Chinese clinical notes
Liu Z, Wang X, Chen Q, Tang B, Xu H. Temporal indexing of medical entity in Chinese clinical notes. BMC Medical Informatics And Decision Making 2019, 19: 17. PMID: 30700331, PMCID: PMC6354334, DOI: 10.1186/s12911-019-0735-x.Peer-Reviewed Original ResearchConceptsSupport vector machineConvolutional neural networkTemporal indexingNeural network modelIndexing taskRelation classificationMedical entitiesRecurrent convolutional neural network modelMachine learning-based systemsConvolutional neural network modelDeep neural network modelNetwork methodNetwork modelLearning-based systemTemporal relation classificationRecurrent neural network methodChinese clinical notesTemporal relationsClinical notesNeural network methodI2b2 NLP challengeContext informationTime indexingSemantic informationBaseline methods
2018
Clinical text annotation - what factors are associated with the cost of time?
Wei Q, Franklin A, Cohen T, Xu H. Clinical text annotation - what factors are associated with the cost of time? AMIA Annual Symposium Proceedings 2018, 2018: 1552-1560. PMID: 30815201, PMCID: PMC6371268.Peer-Reviewed Original ResearchMeSH KeywordsData MiningElectronic Health RecordsHumansLinear ModelsNatural Language ProcessingSemanticsTime FactorsWorkloadConceptsAnnotation timeClinical textNatural language processing modelsClinical corpusIndividual user behaviorEntity recognition taskLanguage processing modelsPractice of annotationCharacteristics of sentencesClinical Text AnnotationText annotationsUser behaviorIndividual usersCost of timeActive learning researchRecognition taskLearning researchProcessing modelCost modelAnnotationUsersLimited workCorpusTextTaskIdentifying 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
Trends and variations in breast and colorectal cancer incidence from 1995 to 2011: A comparative study between Texas Cancer Registry and National Cancer Institute’s Surveillance, Epidemiology and End Results data
LIU Z, ZHANG Y, FRANZIN L, CORMIER J, CHAN W, XU H, DU X. Trends and variations in breast and colorectal cancer incidence from 1995 to 2011: A comparative study between Texas Cancer Registry and National Cancer Institute’s Surveillance, Epidemiology and End Results data. International Journal Of Oncology 2015, 46: 1819-1826. PMID: 25672365, PMCID: PMC4356494, DOI: 10.3892/ijo.2015.2881.Peer-Reviewed Original ResearchConceptsColorectal cancer incidenceNational Cancer Institute's SurveillanceTexas Cancer RegistryBreast cancer incidenceCancer incidenceCancer RegistryAge-adjusted breast cancer incidenceColorectal cancer patientsEnd Results (SEER) dataSEER areasColorectal cancerCancer patientsIncidence rateRelative riskIncidenceBreastRegistrySurveillanceEpidemiologySEERResult dataTemporal trendsEnd resultPatientsParallel comparisonA 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
Opioid Use After Cardiac Surgery in Children With Down Syndrome*
Van Driest S, Shah A, Marshall M, Xu H, Smith A, McGregor T, Kannankeril J. Opioid Use After Cardiac Surgery in Children With Down Syndrome*. Pediatric Critical Care Medicine 2013, 14: 862-868. PMID: 23962833, PMCID: PMC3830692, DOI: 10.1097/pcc.0b013e31829f5d9d.Peer-Reviewed Original ResearchConceptsCardiac bypass timeCumulative opioid dosesOpioid dosesCardiac surgeryDown syndromeOpioid doseBypass timePeak serum creatinine valuesRetrospective observational comparative studyNonsteroidal anti-inflammatory drugsElectronic medical record dataAdditional operative proceduresLonger hospital staySerum creatinine valuesObservational comparative studyPediatric teaching hospitalNeuromuscular blocking agentsMedical record dataAnti-inflammatory drugsOpioid resistanceHospital stayOpioid exposureOpioid medicationsPain scoresLonger hospitalization
2009
Development of a natural language processing system to identify timing and status of colonoscopy testing in electronic medical records.
Denny J, Peterson J, Choma N, Xu H, Miller R, Bastarache L, Peterson N. Development of a natural language processing system to identify timing and status of colonoscopy testing in electronic medical records. AMIA Annual Symposium Proceedings 2009, 2009: 141. PMID: 20351837, PMCID: PMC2815478.Peer-Reviewed Original ResearchConceptsNatural language processingNatural language processing systemsElectronic medical recordsLanguage processing systemNLP systemsIdentifier systemLanguage processingMedical recordsProcessing systemElectronic textsColorectal cancer screening ratesCancer screening ratesPrimary care populationColonoscopy testingScreening ratesCare populationBilling codesQueriesColonoscopySystemStatus indicatorsAlgorithmCodeProcessingStatus