2023
Using annotation for computerized support for fast skimming of cardiology electronic health record notes
Dehkordi M, Einstein A, Zhou S, Elhanan G, Perl Y, Keloth V, Geller J, Liu H. Using annotation for computerized support for fast skimming of cardiology electronic health record notes. 2023, 00: 4043-4050. DOI: 10.1109/bibm58861.2023.10385289.Peer-Reviewed Original ResearchElectronic health recordsElectronic health record notesNamed Entity RecognitionTraining dataMining conceptsInterface terminologyMachine learningSNOMED CTEntity recognitionHealth recordsHealthcare professionalsTransfer learningPatient careCurrent healthcareMining techniquesMining phrasesArt techniquesRecord notesSNOMED conceptsMedical specialtiesComputer-SupportedMedical professionalsReference terminologyCritical informationAnnotationTowards precise PICO extraction from abstracts of randomized controlled trials using a section-specific learning approach
Hu Y, Keloth V, Raja K, Chen Y, Xu H. Towards precise PICO extraction from abstracts of randomized controlled trials using a section-specific learning approach. Bioinformatics 2023, 39: btad542. PMID: 37669123, PMCID: PMC10500081, DOI: 10.1093/bioinformatics/btad542.Peer-Reviewed Original ResearchNatural language processingMicro-F1 scoreCOVID-19 datasetNLP pipelineF1 scoreEntity recognition modelAD datasetPICO elementsSentence classificationNER modelRecognition modelLanguage processingLearning approachLearning modelEnd evaluationSupplementary dataDatasetPipelineExtractionInformationRCT abstractsAnnotationSentencesBioinformaticsComplexityMining of EHR for interface terminology concepts for annotating EHRs of COVID patients
Keloth V, Zhou S, Lindemann L, Zheng L, Elhanan G, Einstein A, Geller J, Perl Y. Mining of EHR for interface terminology concepts for annotating EHRs of COVID patients. BMC Medical Informatics And Decision Making 2023, 23: 40. PMID: 36829139, PMCID: PMC9951157, DOI: 10.1186/s12911-023-02136-0.Peer-Reviewed Original ResearchConceptsElectronic health recordsCoronavirus Infectious Disease OntologyGranular conceptsTextual dataInterface terminologyVolume of textual dataSNOMED CTLack of annotationsMining of electronic health recordsMachine learning modelsInfectious Disease OntologyTraining dataAutomatic annotationAutomatic extractionLearning modelsMining approachHold-out datasetElectronic health record dataCOVID-19 terminologyHealth recordsAnnotationOntologyDisease OntologyDatasetSNOMED
2020
Generating Training Data for Concept-Mining for an ‘Interface Terminology’ Annotating Cardiology EHRs
Keloth V, Zhou S, Einstein A, Elhanan G, Chen Y, Geller J, Perl Y. Generating Training Data for Concept-Mining for an ‘Interface Terminology’ Annotating Cardiology EHRs. 2020, 00: 1728-1735. DOI: 10.1109/bibm49941.2020.9313435.Peer-Reviewed Original ResearchMining Concepts for a COVID Interface Terminology for Annotation of EHRs
Keloth V, Zhou S, Lindemann L, Elhanan G, Einstein A, Geller J, Perl Y. Mining Concepts for a COVID Interface Terminology for Annotation of EHRs. 2020, 00: 3753-3760. DOI: 10.1109/bigdata50022.2020.9377981.Peer-Reviewed Original ResearchInterface terminologyDeluge of medical dataAnnotated clinical notesMachine learning techniquesConcept miningTraining dataClinical textHuge volumesLearning techniquesMining conceptsGranular conceptsMedical dataEHRInitial versionIncomplete dataAnnotationMiningCOVID-19 patientsHealthcare servicesConcatenationHealthcare deliveryDelugeOntologyMachineConcept