2023
Blockchain-enabled immutable, distributed, and highly available clinical research activity logging system for federated COVID-19 data analysis from multiple institutions
Kuo T, Pham A, Edelson M, Kim J, Chan J, Gupta Y, Ohno-Machado L, Anderson D, Balacha C, Bath T, Baxter S, Becker-Pennrich A, Bell D, Bernstam E, Ngan C, Day M, Doctor J, DuVall S, El-Kareh R, Florian R, Follett R, Geisler B, Ghigi A, Gottlieb A, Hinske L, Hu Z, Ir D, Jiang X, Kim K, Kim J, Knight T, Koola J, Kuo T, Lee N, Mansmann U, Matheny M, Meeker D, Mou Z, Neumann L, Nguyen N, Nick A, Ohno-Machado L, Park E, Paul P, Pletcher M, Post K, Rieder C, Scherer C, Schilling L, Soares A, SooHoo S, Soysal E, Steven C, Tep B, Toy B, Wang B, Wu Z, Xu H, Yong C, Zheng K, Zhou Y, Zucker R. Blockchain-enabled immutable, distributed, and highly available clinical research activity logging system for federated COVID-19 data analysis from multiple institutions. Journal Of The American Medical Informatics Association 2023, 30: 1167-1178. PMID: 36916740, PMCID: PMC10198529, DOI: 10.1093/jamia/ocad049.Peer-Reviewed Original ResearchConceptsFederated data analysisUser activity logsSmart contract deploymentRun-time efficiencyData analysis systemData analysis activitiesActivity logsData discoveryQuerying timeBlockchain systemBlockchain technologyNetwork transactionsCOVID-19 data analysisMultiple institutionsLow deploymentBlockchainGitHub repositoryMultiple nodesLarge networksQueriesAnalysis activitiesHigh availabilityLanguage codeBaseline solutionData analysis
2022
Combining human and machine intelligence for clinical trial eligibility querying
Fang Y, Idnay B, Sun Y, Liu H, Chen Z, Marder K, Xu H, Schnall R, Weng C. Combining human and machine intelligence for clinical trial eligibility querying. Journal Of The American Medical Informatics Association 2022, 29: 1161-1171. PMID: 35426943, PMCID: PMC9196697, DOI: 10.1093/jamia/ocac051.Peer-Reviewed Original ResearchConceptsNegation scope detectionCohort queriesScope detectionHealth Information Technology Usability Evaluation ScaleHuman-computer collaborationValue normalizationNatural language processingMachine intelligenceDomain expertsEligibility criteria textUsability evaluationLearnability scoreF1 scoreUser interventionLanguage processingHuman intelligenceUsability scoreQueriesError correctionEngagement featuresIntelligenceDisease trialsFrequent modificationsEnhanced modulesCOVID-19 clinical trials
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
Clinical Word Sense Disambiguation with Interactive Search and Classification.
Wang Y, Zheng K, Xu H, Mei Q. Clinical Word Sense Disambiguation with Interactive Search and Classification. AMIA Annual Symposium Proceedings 2017, 2016: 2062-2071. PMID: 28269966, PMCID: PMC5333264.Peer-Reviewed Original ResearchConceptsDomain knowledgeHuman expertsWSD modelClinical textCurrent active learning methodsWord sense disambiguation systemNatural language processing applicationsMachine learning processLanguage processing applicationsWord sense disambiguationActive learning methodsContextual wordsInteractive searchWord ambiguityLearning methodsSense disambiguationProcessing applicationsAmbiguous instancesSearch processDisambiguation systemEvaluation corpusLearning processExpertsQueriesClassifierInformation retrieval for biomedical datasets: the 2016 bioCADDIE dataset retrieval challenge
Roberts K, Gururaj A, Chen X, Pournejati S, Hersh W, Demner-Fushman D, Ohno-Machado L, Cohen T, Xu H. Information retrieval for biomedical datasets: the 2016 bioCADDIE dataset retrieval challenge. Database 2017, 2017: bax068. DOI: 10.1093/database/bax068.Peer-Reviewed Original ResearchBiomedical datasetsRetrieval challengesInformation retrieval techniquesAdvanced query processingBiomedical data repositoriesAdvanced retrieval methodsQuery processingInformation retrievalTest queriesRetrieval systemRank frameworkRetrieval approachRetrieval techniquesData repositoryRetrieval methodTop precisionDatasetQueriesRepositoryChallengesRetrievalTaskLearningSystemCorpus
2014
PhenDisco: phenotype discovery system for the database of genotypes and phenotypes
Doan S, Lin K, Conway M, Ohno-Machado L, Hsieh A, Feupe S, Garland A, Ross M, Jiang X, Farzaneh S, Walker R, Alipanah N, Zhang J, Xu H, Kim H. PhenDisco: phenotype discovery system for the database of genotypes and phenotypes. Journal Of The American Medical Informatics Association 2014, 21: 31-36. PMID: 23989082, PMCID: PMC3912702, DOI: 10.1136/amiajnl-2013-001882.Peer-Reviewed Original ResearchConceptsNew information retrieval systemInformation retrieval systemsInformation retrieval toolsDatabase of GenotypesText processing toolsRetrieval systemSearch scenariosDiscovery systemRetrieval toolsAuthorized usersNon-standardized wayCross-study validationSearch comparisonProcessing toolsPromising performanceUsersPhenotype informationDatabaseInformationBiotechnology InformationQueriesMetadataEntrezResourcesSystem
2012
DTome: a web-based tool for drug-target interactome construction
Sun J, Wu Y, Xu H, Zhao Z. DTome: a web-based tool for drug-target interactome construction. BMC Bioinformatics 2012, 13: s7. PMID: 22901092, PMCID: PMC3372450, DOI: 10.1186/1471-2105-13-s9-s7.Peer-Reviewed Original ResearchConceptsWeb-based toolUser-friendly web interfaceWeb-based queriesRich data sourceDifferent knowledge basesDatabase schemaWeb interfaceVisualization processKnowledge basesComputational workflowDiscovery processData sourcesNetworkDrug-target interactionsDrugs' primary targetsDrug-target networkWorkflowEarly-stage drug discoveryNetwork analysisQueriesToolPromising approachDrug discovery processSchemaDetailed network analysis
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