Including urinary output to define AKI enhances the performance of machine learning models to predic...
Including urinary output to define AKI enhances the performance of machine learning models to predict AKI at admission
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Full title
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Publisher
United States: Elsevier Inc
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Language
English
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Publisher
United States: Elsevier Inc
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Scope and Contents
Contents
Acute kidney injury (AKI) is a prevalent and detrimental condition in intensive care unit patients. Most AKI predictive models only predict creatinine-triggered AKI (AKICr) and might underperform when predicting urine-output-triggered AKI (AKIUO). We aimed to describe how admission AKICr prediction models perform in all AKI patients.
Three types...
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Full title
Including urinary output to define AKI enhances the performance of machine learning models to predict AKI at admission
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8534813
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8534813
Other Identifiers
ISSN
0883-9441
E-ISSN
1557-8615
DOI
10.1016/j.jcrc.2021.01.003
