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A Bayesian latent class approach for EHR-based phenotyping.
Hubbard, Rebecca A; Huang, Jing; Harton, Joanna; Oganisian, Arman; Choi, Grace; Utidjian, Levon; Eneli, Ihuoma; Bailey, L Charles; Chen, Yong.
Affiliation
  • Hubbard RA; Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Huang J; Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Harton J; Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Oganisian A; Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Choi G; Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Utidjian L; Department of Pediatrics, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Eneli I; Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
  • Bailey LC; Nationwide Children's Hospital, Columbus, Ohio.
  • Chen Y; Department of Pediatrics, University of Pennsylvania, Philadelphia, Pennsylvania.
Stat Med ; 38(1): 74-87, 2019 01 15.
Article de En | MEDLINE | ID: mdl-30252148
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Théorème de Bayes / Dossiers médicaux électroniques / Analyse de structure latente Type d'étude: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limites: Adolescent / Child / Female / Humans / Male Langue: En Journal: Stat Med Année: 2019 Type de document: Article Pays de publication: Royaume-Uni
Texte intégral
Ajouter à My VHL
Imprimer
XML
PubMed Links
Recherche sur Google

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Théorème de Bayes / Dossiers médicaux électroniques / Analyse de structure latente Type d'étude: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limites: Adolescent / Child / Female / Humans / Male Langue: En Journal: Stat Med Année: 2019 Type de document: Article Pays de publication: Royaume-Uni