2023
Automated Identification of Missing IS-A Relations in the Human Phenotype Ontology.
Mohtashamian M, Hu R, Abeysinghe R, Hao X, Xu H, Cui L. Automated Identification of Missing IS-A Relations in the Human Phenotype Ontology. AMIA Annual Symposium Proceedings 2023, 2022: 785-794. PMID: 37128366, PMCID: PMC10148310.Peer-Reviewed Original Research
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
2013
Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data
Denny J, Bastarache L, Ritchie M, Carroll R, Zink R, Mosley J, Field J, Pulley J, Ramirez A, Bowton E, Basford M, Carrell D, Peissig P, Kho A, Pacheco J, Rasmussen L, Crosslin D, Crane P, Pathak J, Bielinski S, Pendergrass S, Xu H, Hindorff L, Li R, Manolio T, Chute C, Chisholm R, Larson E, Jarvik G, Brilliant M, McCarty C, Kullo I, Haines J, Crawford D, Masys D, Roden D. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nature Biotechnology 2013, 31: 1102-1111. PMID: 24270849, PMCID: PMC3969265, DOI: 10.1038/nbt.2749.Peer-Reviewed Original ResearchApplying active learning to high-throughput phenotyping algorithms for electronic health records data
Chen Y, Carroll R, Hinz E, Shah A, Eyler A, Denny J, Xu H. Applying active learning to high-throughput phenotyping algorithms for electronic health records data. Journal Of The American Medical Informatics Association 2013, 20: e253-e259. PMID: 23851443, PMCID: PMC3861916, DOI: 10.1136/amiajnl-2013-001945.Peer-Reviewed Original ResearchConceptsActive learningUnrefined featuresSupervised Machine Learning AlgorithmsRefined featuresPhenotyping algorithmElectronic health record dataMachine Learning AlgorithmsHealth record dataVenous thromboembolismRheumatoid arthritisFeature engineeringDomain expertsDomain knowledgePhenotyping tasksLearning algorithmFeature setsLearning approachColorectal cancerAL approachCurve scorePassive learning approachHigh-throughput phenotyping methodsAlgorithmSmall setRecord dataCharacterization of Statin Dose Response in Electronic Medical Records
Wei W, Feng Q, Jiang L, Waitara M, Iwuchukwu O, Roden D, Jiang M, Xu H, Krauss R, Rotter J, Nickerson D, Davis R, Berg R, Peissig P, McCarty C, Wilke R, Denny J. Characterization of Statin Dose Response in Electronic Medical Records. Clinical Pharmacology & Therapeutics 2013, 95: 331-338. PMID: 24096969, PMCID: PMC3944214, DOI: 10.1038/clpt.2013.202.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAllelesAtorvastatinCholesterol, LDLCohort StudiesDatabases, FactualDose-Response Relationship, DrugElectronic Health RecordsGenotypeHeptanoic AcidsHumansHydroxymethylglutaryl-CoA Reductase InhibitorsHyperlipidemiasLipid MetabolismLipidsPhenotypePolymorphism, Single NucleotidePyrrolesRandomized Controlled Trials as TopicSimvastatin
2012
Electronic Medical Records as a Tool in Clinical Pharmacology: Opportunities and Challenges
Roden D, Xu H, Denny J, Wilke R. Electronic Medical Records as a Tool in Clinical Pharmacology: Opportunities and Challenges. Clinical Pharmacology & Therapeutics 2012, 91: 1083-1086. PMID: 22534870, PMCID: PMC3819803, DOI: 10.1038/clpt.2012.42.Peer-Reviewed Original Research
2006
Natural language processing and visualization in the molecular imaging domain
Tulipano P, Tao Y, Millar W, Zanzonico P, Kolbert K, Xu H, Yu H, Chen L, Lussier Y, Friedman C. Natural language processing and visualization in the molecular imaging domain. Journal Of Biomedical Informatics 2006, 40: 270-281. PMID: 17084109, DOI: 10.1016/j.jbi.2006.08.002.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCell LineComputational BiologyDatabases, BibliographicDatabases, GeneticDiagnostic ImagingGenomicsHumansInformation Storage and RetrievalNatural Language ProcessingPhenotypeProgramming LanguagesSoftwareSystems IntegrationTerminology as TopicUser-Computer InterfaceVocabulary, ControlledConceptsImaging domainNatural language processing systemsNatural language processingLanguage processing systemJava viewerNLP systemsFormal evaluation studiesLanguage processingInformation resourcesProcessing systemMedical imagingIndex imagesSystem performanceBiological informationInformationImagesVisualizationBioMedLEEPerformanceNLPEvaluation studyDomainGenomics literatureSystemSimultaneous visualization