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Improving patient safety via automated laboratory-based adverse event grading
The identification and grading of adverse events (AEs) during the conduct of clinical trials is a labor-intensive and error-prone process. This paper describes and evaluates a software tool developed by City of Hope to automate complex algorithms to assess laboratory results and identify and grade A...
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| Main Authors: | , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BMJ Group
2011
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3240768/ https://ncbi.nlm.nih.gov/pubmed/22084201 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1136/amiajnl-2011-000513 |
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