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Automated identification of implausible values in growth data from pediatric electronic health records

OBJECTIVE: Large electronic health record (EHR) datasets are increasingly used to facilitate research on growth, but measurement and recording errors can lead to biased results. We developed and tested an automated method for identifying implausible values in pediatric EHR growth data. MATERIALS AND...

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Dades bibliogràfiques
Publicat a:J Am Med Inform Assoc
Autors principals: Daymont, Carrie, Ross, Michelle E, Russell Localio, A, Fiks, Alexander G, Wasserman, Richard C, Grundmeier, Robert W
Format: Artigo
Idioma:Inglês
Publicat: Oxford University Press 2017
Matèries:
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC7651915/
https://ncbi.nlm.nih.gov/pubmed/28453637
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocx037
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