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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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| 出版年: | J Am Med Inform Assoc |
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| 主要な著者: | , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Oxford University Press
2017
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| 主題: | |
| オンライン･アクセス: | 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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