A systematic review of artificial intelligence algorithms for predicting acute kidney injury.
Journal:
European review for medical and pharmacological sciences
Published Date:
Oct 1, 2023
Abstract
OBJECTIVE: Acute kidney injury (AKI) increases mortality and costs in hospitalized patients. New methods for early AKI identification have been developed with targeted biomarkers and electronic health records data analysis. Machine learning (ML) use in diagnostics and health data analysis has recently increased. We performed a systematic review to analyze the use of ML for AKI prediction in hospitalized adults.