2021
A Discrete Joint Model for Entity and Relation Extraction from Clinical Notes.
Ji Z, Ghiasvand O, Wu S, Xu H. A Discrete Joint Model for Entity and Relation Extraction from Clinical Notes. AMIA Joint Summits On Translational Science Proceedings 2021, 2021: 315-324. PMID: 34457146, PMCID: PMC8378610.Peer-Reviewed Original ResearchConceptsRelation classificationPipeline architectureClinical natural language processingNatural language processingEntity recognitionBeam searchRelation extractionClinical notesLanguage processingClassification stepEntity pairsStructured perceptronFundamental taskClinical narrativesTraditional solutionsRecognition stepError propagationArchitectureJoint modelTaskSubtasksPerceptronClinical conceptsEntitiesClassification
2019
Applying a deep learning-based sequence labeling approach to detect attributes of medical concepts in clinical text
Xu J, Li Z, Wei Q, Wu Y, Xiang Y, Lee H, Zhang Y, Wu S, Xu H. Applying a deep learning-based sequence labeling approach to detect attributes of medical concepts in clinical text. BMC Medical Informatics And Decision Making 2019, 19: 236. PMID: 31801529, PMCID: PMC6894107, DOI: 10.1186/s12911-019-0937-2.Peer-Reviewed Original ResearchConceptsSequence labeling approachMedical conceptsEntity recognitionRelation classificationClinical textDetection taskBidirectional long short-term memory networkLong short-term memory networkShort-term memory networkConditional Random FieldsSequence labeling problemTraditional methodsNLP applicationsBi-LSTMNeural architectureLabeling problemLabeling approachMemory networkNovel solutionRandom fieldsHigh accuracyEfficient wayTaskAttributesClassification
2015
Classification of Cancer Primary Sites Using Machine Learning and Somatic Mutations
Chen Y, Sun J, Huang L, Xu H, Zhao Z. Classification of Cancer Primary Sites Using Machine Learning and Somatic Mutations. BioMed Research International 2015, 2015: 491502. PMID: 26539502, PMCID: PMC4619847, DOI: 10.1155/2015/491502.Peer-Reviewed Original ResearchConceptsMachine learningF-measureAvailable big dataSupport vector machineBig dataVector machineClassification experimentsAccurate classificationCancer classificationGene function informationMachineSomatic mutation informationClassificationMutation informationFunction informationLearningGene symbolsInformationGene featuresGreat opportunityPerformanceSomatic mutation dataMutation dataAccuracyPrediction
2012
A study of transportability of an existing smoking status detection module across institutions.
Liu M, Shah A, Jiang M, Peterson N, Dai Q, Aldrich M, Chen Q, Bowton E, Liu H, Denny J, Xu H. A study of transportability of an existing smoking status detection module across institutions. AMIA Annual Symposium Proceedings 2012, 2012: 577-86. PMID: 23304330, PMCID: PMC3540509.Peer-Reviewed Original ResearchConceptsDetection moduleNatural language processing systemsKnowledge Extraction SystemEMR dataRule-based classifierClinical Text AnalysisHighest F-measureLanguage processing systemElectronic medical recordsF-measureLevels of classificationProcessing systemSpecific tasksText analysisClassifierDesirable performanceModuleModest effortExtraction systemCTAKESSmoking moduleMachineSystemTaskClassification