Abstract:BackgroundAcute Kidney Injury (AKI), a major public health problem,is responsible for two-thirds of intensive care unit patients’ cost, and aging is an independent risk factor for AKI and its associated mortality and morbidity. The early recognition of AKI helps ICU caregivers to guide fluid treatment and titrate the dosing of the nephrotoxic drug. Therefore, it is desirable to build models to predict their position. The study is to build models based machine learning to predict AKI stage after 24 hours and 48… Show more
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