This study developed and validated a machine learning model to differentiate between acute kidney injury (AKI) and functional decline (FD) in children with urinary tract infection (UTI). The model utilized clinical and laboratory data to improve diagnostic accuracy. The findings suggest that the model effectively distinguishes between AKI and FD, highlighting the potential for improved clinical decision-making.
Publisher
JAMA Network Open
Published On
Jul 27, 2023
Authors
Tsai CM
Tags
acute kidney injury
functional decline
machine learning
children health
urinary tract infection
diagnostic accuracy
clinical decision-making
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