2024
Detection of Gastrointestinal Bleeding with Large Language Models to Aid Quality Improvement and Appropriate Reimbursement
Zheng N, Keloth V, You K, Kats D, Li D, Deshpande O, Sachar H, Xu H, Laine L, Shung D. Detection of Gastrointestinal Bleeding with Large Language Models to Aid Quality Improvement and Appropriate Reimbursement. Gastroenterology 2024 PMID: 39304088, DOI: 10.1053/j.gastro.2024.09.014.Peer-Reviewed Original ResearchElectronic health recordsOvert gastrointestinal bleedingGastrointestinal bleedingRecurrent bleedingMachine learning modelsHealth recordsClinically relevant applicationsNursing notesLanguage modelAcute gastrointestinal bleedingQuality improvementLearning modelsDetection of gastrointestinal bleedingReimbursementIdentification of clinical conditionsSeparate hospitalsQuality measuresHospitalBleedingClinical conditionsPatient managementEarly identificationPatientsReimbursement codesCoding algorithm1244 AUTOMATED IDENTIFICATION OF RECURRENT GASTROINTESTINAL BLEEDING USING ELECTRONIC HEALTH RECORDS AND LARGE LANGUAGE MODELS
Zheng N, Keloth V, You K, Li D, Xu H, Laine L, Shung D. 1244 AUTOMATED IDENTIFICATION OF RECURRENT GASTROINTESTINAL BLEEDING USING ELECTRONIC HEALTH RECORDS AND LARGE LANGUAGE MODELS. Gastroenterology 2024, 166: s-292. DOI: 10.1016/s0016-5085(24)01152-1.Peer-Reviewed Original ResearchSkimming of Electronic Health Records Highlighted by an Interface Terminology Curated with Machine Learning Mining
Koohi H. Dehkordi M, Kollapally N, Perl Y, Geller J, Deek F, Liu H, Keloth V, Elhanan G, Einstein A. Skimming of Electronic Health Records Highlighted by an Interface Terminology Curated with Machine Learning Mining. 2024, 498-505. DOI: 10.5220/0012391600003657.Peer-Reviewed Original Research
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 informationAnnotationRepresenting and utilizing clinical textual data for real world studies: An OHDSI approach
Keloth V, Banda J, Gurley M, Heider P, Kennedy G, Liu H, Liu F, Miller T, Natarajan K, V Patterson O, Peng Y, Raja K, Reeves R, Rouhizadeh M, Shi J, Wang X, Wang Y, Wei W, Williams A, Zhang R, Belenkaya R, Reich C, Blacketer C, Ryan P, Hripcsak G, Elhadad N, Xu H. Representing and utilizing clinical textual data for real world studies: An OHDSI approach. Journal Of Biomedical Informatics 2023, 142: 104343. PMID: 36935011, PMCID: PMC10428170, DOI: 10.1016/j.jbi.2023.104343.Peer-Reviewed Original ResearchConceptsNatural language processingCommon data modelTextual dataNLP solutionObservational Health Data SciencesOMOP Common Data ModelSpecific use casesObservational Medical Outcomes Partnership Common Data ModelHealth Data SciencesRepresentation of informationUse casesElectronic health recordsReal-world evidence generationData scienceClinical textData modelClinical notesLanguage processingHealth recordsLoad dataClinical documentationCurrent applicationsInformationWorkflowEvidence generationMining 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