2016
Automated identification of molecular effects of drugs (AIMED)
Fathiamini S, Johnson A, Zeng J, Araya A, Holla V, Bailey A, Litzenburger B, Sanchez N, Khotskaya Y, Xu H, Meric-Bernstam F, Bernstam E, Cohen T. Automated identification of molecular effects of drugs (AIMED). Journal Of The American Medical Informatics Association 2016, 23: 758-765. PMID: 27107438, PMCID: PMC4926748, DOI: 10.1093/jamia/ocw030.Peer-Reviewed Original Research
2014
Identifying plausible adverse drug reactions using knowledge extracted from the literature
Shang N, Xu H, Rindflesch T, Cohen T. Identifying plausible adverse drug reactions using knowledge extracted from the literature. Journal Of Biomedical Informatics 2014, 52: 293-310. PMID: 25046831, PMCID: PMC4261011, DOI: 10.1016/j.jbi.2014.07.011.Peer-Reviewed Original ResearchConceptsPredication-based Semantic IndexingReflective Random IndexingLBD methodsNatural language processing toolsBiomedical literatureDrug-adverse event associationsLanguage processing toolsSemantic indexingElectronic health recordsRandom IndexingHuman reviewVast repositoryDiscovery methodsVolume of knowledgeProcessing toolsEvaluation setHealth recordsData sourcesEvent associationsIndexingDrug-effect relationshipsRepositoryLarge volumesADR associationsReasoning pathwaysEvaluating 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
2013
Applying active learning to supervised word sense disambiguation in MEDLINE
Chen Y, Cao H, Mei Q, Zheng K, Xu H. Applying active learning to supervised word sense disambiguation in MEDLINE. Journal Of The American Medical Informatics Association 2013, 20: 1001-1006. PMID: 23364851, PMCID: PMC3756255, DOI: 10.1136/amiajnl-2012-001244.Peer-Reviewed Original Research
2011
RANKING GENE-DRUG RELATIONSHIPS IN BIOMEDICAL LITERATURE USING LATENT DIRICHLET ALLOCATION
Altman R, Dunker A, Hunter L, Murray T, Klein T, WU Y, LIU M, ZHENG W, ZHAO Z, XU H. RANKING GENE-DRUG RELATIONSHIPS IN BIOMEDICAL LITERATURE USING LATENT DIRICHLET ALLOCATION. Biocomputing 2011, 422-33. PMID: 22174297, PMCID: PMC4095990, DOI: 10.1142/9789814366496_0041.Peer-Reviewed Original Research
2007
Automated Acquisition of Disease–Drug Knowledge from Biomedical and Clinical Documents: An Initial Study
Chen E, Hripcsak G, Xu H, Markatou M, Friedman C. Automated Acquisition of Disease–Drug Knowledge from Biomedical and Clinical Documents: An Initial Study. Journal Of The American Medical Informatics Association 2007, 15: 87-98. PMID: 17947625, PMCID: PMC2274872, DOI: 10.1197/jamia.m2401.Peer-Reviewed Original ResearchA study of abbreviations in clinical notes.
Xu H, Stetson P, Friedman C. A study of abbreviations in clinical notes. AMIA Annual Symposium Proceedings 2007, 2007: 821-5. PMID: 18693951, PMCID: PMC2655910.Peer-Reviewed Original ResearchConceptsUnified Medical Language SystemNatural language processing systemsLanguage processing systemNarrative clinical notesDetection methodClinical notesDifferent knowledge sourcesSense inventoryDomain expertsNLP systemsCorrect sensesDecision supportText corporaKnowledge sourcesError detectionProcessing systemBiomedical literatureStudy of abbreviationsLanguage systemPatient informationAmbiguity rateBetter detection methodsDatabaseAnnotationAbbreviationsGene symbol disambiguation using knowledge-based profiles
Xu H, Fan J, Hripcsak G, Mendonça E, Markatou M, Friedman C. Gene symbol disambiguation using knowledge-based profiles. Bioinformatics 2007, 23: 1015-1022. PMID: 17314123, DOI: 10.1093/bioinformatics/btm056.Peer-Reviewed Original ResearchConceptsKnowledge sourcesSimilarity scoresInformation retrieval methodsGene symbol disambiguationText mining systemKnowledge-based profilesTesting data setsBiomedical entitiesBiomedical domainMEDLINE abstractsHigh similarity scoresRetrieval methodAmbiguous genesEntrez GeneGene symbolsDisambiguation taskTesting set