Machine learning for the prediction of acute kidney injury in critical care patients with acute cere...
Machine learning for the prediction of acute kidney injury in critical care patients with acute cerebrovascular disease
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Author / Creator
Publisher
England: Taylor & Francis
Journal title
Language
English
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Publisher
England: Taylor & Francis
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Scope and Contents
Contents
Acute kidney injury (AKI) is a common complication and associated with a poor clinical outcome. In this study, we developed and validated a model for predicting the risk of AKI through machine learning methods in critical care patients with acute cerebrovascular disease.
This study was a retrospective study based on two different cohorts. Five m...
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Full title
Machine learning for the prediction of acute kidney injury in critical care patients with acute cerebrovascular disease
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Record Identifier
TN_cdi_crossref_citationtrail_10_1080_0886022X_2022_2036619
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_citationtrail_10_1080_0886022X_2022_2036619
Other Identifiers
ISSN
0886-022X
E-ISSN
1525-6049
DOI
10.1080/0886022X.2022.2036619
