Machine Learning Predicts Acute Kidney Injury in Hospitalized Patients with Sickle Cell Disease

CONCLUSION: XGBoost accurately predicted AKI as early as 12 hours before onset in hospitalized SCD patients and may enable the development of innovative prevention strategies.PMID:37906980 | DOI:10.1159/000534864

Source: American Journal of Nephrology - October 31, 2023 Category: Urology & Nephrology Authors: Rima S Zahr Akram Mohammed Surabhi Naik Daniel Faradji Kenneth I Ataga Jeffrey Lebensburger Robert L Davis Source Type: research