Internal and external validation of a machine learning risk score for acute kidney injury
Importance Acute kidney injury (AKI) is associated with increased morbidity and mortality in
hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and
few prediction models have been externally validated. Objective To internally and externally
validate a machine learning risk score to detect AKI in hospitalized patients. Design, Setting,
and Participants This diagnostic study included 495 971 adult hospital admissions at the
University of Chicago (UC) from 2008 to 2016 (n= 48 463), at Loyola University Medical …
hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and
few prediction models have been externally validated. Objective To internally and externally
validate a machine learning risk score to detect AKI in hospitalized patients. Design, Setting,
and Participants This diagnostic study included 495 971 adult hospital admissions at the
University of Chicago (UC) from 2008 to 2016 (n= 48 463), at Loyola University Medical …
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