2024
Towards Enhanced Topic Discovery on Semantic Maps for Biomedical Literature Exploration
Choi B, Ondov B, He H, Xu H. Towards Enhanced Topic Discovery on Semantic Maps for Biomedical Literature Exploration. 2024, 00: 25-27. DOI: 10.1109/vahc65315.2024.00015.Peer-Reviewed Original ResearchSemantic mapHierarchical topic modelTF-IDF methodCentroid-based methodHierarchical topicsTopic discoveryGrowth of biomedical researchLabel generationTopic treeTopic modelsOverwhelming volumeNovel methodHierarchical clusteringPublic distributionLiterature explorationSemanticsMapsEnhanced visualizationHDBSCANTopicsLabelingMethodRepresentationVisualizationVolume of literature
2020
Time 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
2017
Expressing 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
2014
Evaluating Word Representation Features in Biomedical Named Entity Recognition Tasks
Tang B, Cao H, Wang X, Chen Q, Xu H. Evaluating Word Representation Features in Biomedical Named Entity Recognition Tasks. BioMed Research International 2014, 2014: 240403. PMID: 24729964, PMCID: PMC3963372, DOI: 10.1155/2014/240403.Peer-Reviewed Original ResearchConceptsBiomedical Named Entity RecognitionWord representationsNamed Entity Recognition (NER) taskMachine learning-based approachWord representation featuresNatural language processingLearning-based approachEntity recognition taskNamed Entity RecognitionCluster-based representationJNLPBA corpusEntity recognitionBiomedical domainF-measureLanguage processingRepresentation featuresWord embeddingsRecognition taskWR algorithmDistributional representationsTaskBetter performanceAlgorithmRepresentationDifferent types
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply