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Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method
BACKGROUND: Big data tools provide opportunities to monitor adverse events (patient harm associated with medical care) (AEs) in the unstructured text of electronic health care records (EHRs). Writers may explicitly state an apparent association between treatment and adverse outcome (“attributed”) or...
Autores principales: | Bright, Roselie A, Rankin, Summer K, Dowdy, Katherine, Blok, Sergey V, Bright, Susan J, Palmer, Lee Anne M |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10414364/ https://www.ncbi.nlm.nih.gov/pubmed/37725533 http://dx.doi.org/10.2196/27017 |
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