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...

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Bibliographic Details
Published in:Can J Kidney Health Dis
Main Authors: 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.
Format: Artigo
Language:Inglês
Published: BioMed Central 2016
Subjects:
Review
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC4768420/
https://ncbi.nlm.nih.gov/pubmed/26925247
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s40697-016-0099-4
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