Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machin...
Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machine learning
About this item
Full title
Author / Creator
Publisher
England: Oxford University Press
Journal title
Language
English
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Publication information
Publisher
England: Oxford University Press
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More information
Scope and Contents
Contents
Acute kidney injury (AKI) carries a poor prognosis. Its incidence is increasing in the intensive care unit (ICU). Our purpose in this study is to develop and externally validate a model for predicting AKI in the ICU using patient data present prior to ICU admission.
We used data of 98 472 adult ICU admissions at Mayo Clinic between 1 January 200...
Alternative Titles
Full title
Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machine learning
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8087133
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8087133
Other Identifiers
ISSN
2048-8505
E-ISSN
2048-8513
DOI
10.1093/ckj/sfaa145
