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Utilizing electronic health records to predict acute kidney injury risk and outcomes: workgroup statements from the 15(th) ADQI Consensus Conference
The data contained within the electronic health record (EHR) is “big” from the standpoint of volume, velocity, and variety. These circumstances and the pervasive trend towards EHR adoption have sparked interest in applying big data predictive analytic techniques to EHR data. Acute kidney injury (AKI...
Autores principales: | Sutherland, Scott M., Chawla, Lakhmir S., Kane-Gill, Sandra L., Hsu, Raymond K., Kramer, Andrew A., Goldstein, Stuart L., Kellum, John A., Ronco, Claudio, Bagshaw, Sean M. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4768420/ https://www.ncbi.nlm.nih.gov/pubmed/26925247 http://dx.doi.org/10.1186/s40697-016-0099-4 |
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