2021
Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules
Shung D, Tsay C, Laine L, Chang D, Li F, Thomas P, Partridge C, Simonov M, Hsiao A, Tay JK, Taylor A. Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules. Journal Of Gastroenterology And Hepatology 2021, 36: 1590-1597. PMID: 33105045, DOI: 10.1111/jgh.15313.Peer-Reviewed Original ResearchConceptsNatural language processingElectronic health recordsLanguage processingNLP algorithmSystematized NomenclatureReal timeAcute gastrointestinal bleedingBidirectional Encoder RepresentationsDecision rulesEHR-based phenotyping algorithmsGastrointestinal bleedingRisk stratification scoresEncoder RepresentationsData elementsPhenotyping algorithmStratification scoresHealth recordsAlgorithmPhenotyping of patientsEmergency department patientsTime of presentationRisk stratification modelED reviewDeploymentExternal validation
2015
A spatiotemporal quantile regression model for emergency department expenditures
Neelon B, Li F, Burgette LF, Neelon SE. A spatiotemporal quantile regression model for emergency department expenditures. Statistics In Medicine 2015, 34: 2559-2575. PMID: 25782041, DOI: 10.1002/sim.6480.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremBiostatisticsComputer SimulationEmergency Service, HospitalFemaleHealth ExpendituresHumansLikelihood FunctionsMaleModels, StatisticalNorth CarolinaRegression AnalysisConceptsQuantile regression modelSmall area estimationAsymmetric Laplace distributionSpatiotemporal random effectsFull conditionalsRandom effectsBayesian modeling approachLaplace distributionAutoregressive priorsSampling schemeResponse distributionEmergency department expendituresSpatiotemporal smoothingModeling approach