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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Autores principales: Niland, Joyce C, Stiller, Tracey, Neat, Jennifer, Londrc, Adina, Johnson, Dina, Pannoni, Susan
Formato: Artigo
Lenguaje:Inglês
Publicado: BMJ Group 2011
Materias:
Brief Communication
Acceso en línea: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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