Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models
Iscoe M, Socrates V, Gilson A, Chi L, Li H, Huang T, Kearns T, Perkins R, Khandjian L, Taylor R. Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models. Academic Emergency Medicine 2024, 31: 599-610. PMID: 38567658, DOI: 10.1111/acem.14883.Peer-Reviewed Original ResearchElectronic health recordsNatural language processingNatural language processing modelsEmergency departmentTransformer-based modelsClinical notesF1-measureClinical decision supportLanguage modelSpaCy modelsU.S. health systemElements of natural language processingPublic health surveillanceConvolutional neural network-based modelProcessing long documentsIdentification of symptomsHealth recordsHealth systemClinician notesNeural network-based modelMedical careHealth surveillanceSymptom identificationEntity recognitionNetwork-based modelFormative evaluation of an emergency department clinical decision support system for agitation symptoms: a study protocol
Wong A, Nath B, Shah D, Kumar A, Brinker M, Faustino I, Boyce M, Dziura J, Heckmann R, Yonkers K, Bernstein S, Adapa K, Taylor R, Ovchinnikova P, McCall T, Melnick E. Formative evaluation of an emergency department clinical decision support system for agitation symptoms: a study protocol. BMJ Open 2024, 14: e082834. PMID: 38373857, PMCID: PMC10882402, DOI: 10.1136/bmjopen-2023-082834.Peer-Reviewed Original ResearchConceptsComputerised clinical decision supportED treatRestraint useExperiences of restraint useMental health-related visitsEmergency departmentPrevent agitationSystems-related factorsImprove patient experienceClinical decision support systemsRegional health systemClinical decision supportDe-escalation techniquesRandomised controlled trialsFormative evaluationPeer-reviewed journalsBest-practice guidanceAt-risk populationsCDS toolsThematic saturationED cliniciansPatient experienceED sitesHealth systemED physicians