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41250 Machine Learning to Identify Predictors of Iatrogenic Injury Using Empirical Bayes Estimates: A Cohort Study of Pressure Injury Prevention

ABSTRACT IMPACT: A machine learning approach using electronic health records can combine descriptive, population-level factors of pressure injury outcomes. OBJECTIVES/GOALS: Pressure injuries cause 60,000 deaths and cost $26 billion annually in the US, but prevention is laborious. We used clinical d...

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Detalles Bibliográficos
Autores principales:	Padula, William V., Armstrong, David G., Davidson, Patricia M.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Cambridge University Press 2021
Materias:	Data Science/Biostatistics/Informatics
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8827776/ http://dx.doi.org/10.1017/cts.2021.530

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