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
2017
Development and validation of a continuously age-adjusted measure of patient condition for hospitalized children using the electronic medical record
Rothman MJ, Tepas JJ, Nowalk AJ, Levin JE, Rimar JM, Marchetti A, Hsiao AL. Development and validation of a continuously age-adjusted measure of patient condition for hospitalized children using the electronic medical record. Journal Of Biomedical Informatics 2017, 66: 180-193. PMID: 28057565, DOI: 10.1016/j.jbi.2016.12.013.Peer-Reviewed Original ResearchConceptsUnplanned ICU transfersPediatric Rothman IndexElectronic medical recordsRothman IndexICU transferPediatric RiskClinical statusPediatric hospitalHospitalized childrenMedical recordsPRI scoresPatient's conditionMortality dataPost-discharge mortalityPatient's clinical statusMortality odds ratioHospital mortalityInpatient visitsPatient ageAdult mortality dataClinical variablesOdds ratioClinical dataPhysiologic deteriorationPatient acuity