2024
Medical Concept Normalization
Xu H, Demner Fushman D, Hong N, Raja K. Medical Concept Normalization. Cognitive Informatics In Biomedicine And Healthcare 2024, 137-164. DOI: 10.1007/978-3-031-55865-8_6.Peer-Reviewed Original ResearchConcept normalizationDeep learning-based techniquesMedical concept normalizationLearning-based techniquesContemporary machine learningRule-based methodologyAnnotated corpusNLP systemsMachine learningComputing applicationsBiomedical terminologiesNormalization approachStandardized terminologyOntologyTaskLearningMapping 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 ResearchConceptsDocument 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 careFrameworkLOINCStandardizing Multi-site Clinical Note Titles to LOINC Document Ontology: A Transformer-based Approach.
Zuo X, Zhou Y, Duke J, Hripcsak G, Shah N, Banda J, Reeves R, Miller T, Waitman L, Natarajan K, Xu H. Standardizing Multi-site Clinical Note Titles to LOINC Document Ontology: A Transformer-based Approach. AMIA Annual Symposium Proceedings 2024, 2023: 834-843. PMID: 38222429, PMCID: PMC10785935.Peer-Reviewed Original Research
2020
Conversational ontology operator: patient-centric vaccine dialogue management engine for spoken conversational agents
Amith M, Lin R, Cui L, Wang D, Zhu A, Xiong G, Xu H, Roberts K, Tao C. Conversational ontology operator: patient-centric vaccine dialogue management engine for spoken conversational agents. BMC Medical Informatics And Decision Making 2020, 20: 259. PMID: 33317519, PMCID: PMC7734717, DOI: 10.1186/s12911-020-01267-y.Peer-Reviewed Original ResearchConceptsDialogue engineUser-centric systemOntology-based systemQuestion-answering systemManagement engineSoftware engineQuestion AnsweringConversational agentsDialogue interactionCompetency questionsContextual informationConsumer usersCore taskAccuracy scoresConsumer questionsEngineConversational flowHealth informationSimulation trialsInformationUsersFuture plansNext stepOntologyWizardTime event ontology (TEO): to support semantic representation and reasoning of complex temporal relations of clinical events
Li F, Du J, He Y, Song H, Madkour M, Rao G, Xiang Y, Luo Y, Chen H, Liu S, Wang L, Liu H, Xu H, Tao C. Time event ontology (TEO): to support semantic representation and reasoning of complex temporal relations of clinical events. Journal Of The American Medical Informatics Association 2020, 27: 1046-1056. PMID: 32626903, PMCID: PMC7647306, DOI: 10.1093/jamia/ocaa058.Peer-Reviewed Original ResearchConceptsTime Event OntologyComplex temporal relationsEvent ontologyNatural language processing fieldTemporal relationsTime-related queriesInformation annotationProcessing fieldTemporal informationData propertiesRelation representationClinical narrativesSemantic representationElectronic health record dataRich setHealth record dataOntologyStrong capabilityReasoningSetQueriesOrder relationRecord dataRepresentationPrimitives
2019
An Ontology-Powered Dialogue Engine For Patient Communication of Vaccines.
Amith M, Lin R, Cui L, Wang D, Zhu A, Xiong G, Xu H, Roberts K, Tao C. An Ontology-Powered Dialogue Engine For Patient Communication of Vaccines. CEUR Workshop Proceedings 2019, 2427: 24-30. PMID: 32704245, PMCID: PMC7376741.Peer-Reviewed Original ResearchDialogue engineSoftware componentsSoftware engineSpeech interfaceInteraction functionalitiesConversational agentsLive environmentEngine interactionHPV vaccine counselingHPV vaccination ratesLife-threatening cancerOntologyPrevious methodsVaccine counselingVaccination ratesFunctional abilityEnginePatient communicationUnprotected individuals
2017
Lightweight predicate extraction for patient-level cancer information and ontology development
Amith M, Song H, Zhang Y, Xu H, Tao C. Lightweight predicate extraction for patient-level cancer information and ontology development. BMC Medical Informatics And Decision Making 2017, 17: 73. PMID: 28699547, PMCID: PMC5506564, DOI: 10.1186/s12911-017-0465-x.Peer-Reviewed Original ResearchConceptsOntological knowledgebaseKnowledge triplesInformation extraction toolsDevelopment of ontologiesNatural language domainRDF representationSoftware libraryOntology developmentCustom applicationsOntologyDevelopment processExtraction toolAccurate extractionPublic health domainKnowledgebaseTextual sourcesTriplesKnowledgebasesHealth domainsToolExtractionTaskMethodsThis paperMedlinePlusDomainKnowledge-Based Approach for Named Entity Recognition in Biomedical Literature: A Use Case in Biomedical Software Identification
Amith M, Zhang Y, Xu H, Tao C. Knowledge-Based Approach for Named Entity Recognition in Biomedical Literature: A Use Case in Biomedical Software Identification. Lecture Notes In Computer Science 2017, 10351: 386-395. DOI: 10.1007/978-3-319-60045-1_40.Peer-Reviewed Original ResearchEntity recognitionNatural language processingContextual semantic informationNamed Entity RecognitionEntity recognition methodFeatures of ontologyMachine learning approachesKnowledge-based approachSoftware entitiesSoftware namesInformation extractionUse casesBiomedical softwareSemantic informationSoftware identificationLanguage processingRecognition methodLearning approachBiomedical literatureRecognitionOntologyEntitiesSoftwareResearch abstractsTaskExpressing Biomedical Ontologies in Natural Language for Expert Evaluation.
Amith M, Manion F, Harris M, Zhang Y, Xu H, Tao C. Expressing Biomedical Ontologies in Natural Language for Expert Evaluation. 2017, 245: 838-842. PMID: 29295217, PMCID: PMC6644701.Peer-Reviewed Original Research
2007
Using contextual and lexical features to restructure and validate the classification of biomedical concepts
Fan J, Xu H, Friedman C. Using contextual and lexical features to restructure and validate the classification of biomedical concepts. BMC Bioinformatics 2007, 8: 264. PMID: 17650333, PMCID: PMC2014782, DOI: 10.1186/1471-2105-8-264.Peer-Reviewed Original ResearchConceptsUnified Medical Language SystemString-based approachesMean reciprocal rankReciprocal rankNatural language processingError rateContextual featuresLexical featuresIntegration of dataLow error rateReasoning systemAutomatic approachComplementary classifiersLanguage processingClassification approachBiomedical terminologiesClassification errorOntological conceptsBiomedical conceptsOntological termsSyntactic approachLanguage systemClassifierSyntactic featuresOntology