Predicting pediatric cardiac surgery-associated acute kidney injury using machine learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Nephrology,Pediatrics, Perinatology and Child Health
Link
https://link.springer.com/content/pdf/10.1007/s00467-023-06197-1.pdf
Reference24 articles.
1. Li S, Krawczeski CD, Zappitelli M et al (2011) Incidence, risk factors, and outcomes of acute kidney injury after pediatric cardiac surgery – a prospective multicenter study. Crit Care Med 39:1493–1499. https://doi.org/10.1097/CCM.0b013e31821201d3
2. Fuhrman DY, Kellum JA (2017) Epidemiology and pathophysiology of cardiac surgery-associated acute kidney injury. Curr Opin Anesthesiol 30:60–65. https://doi.org/10.1097/ACO.0000000000000412
3. Alten JA, Cooper DS, Blinder JJ et al (2021) Epidemiology of acute kidney injury after neonatal cardiac surgery: a report from the multicenter neonatal and pediatric heart and renal outcomes network. Crit Care Med 49:e941–e951. https://doi.org/10.1097/CCM.0000000000005165
4. Dong J, Feng T, Thapa-Chhetry B et al (2021) Machine learning model for early prediction of acute kidney injury (AKI) in pediatric critical care. Crit Care 25:288. https://doi.org/10.1186/s13054-021-03724-0
5. Deng Y-H, Luo X-Q, Yan P et al (2022) Outcome prediction for acute kidney injury among hospitalized children via eXtreme Gradient Boosting algorithm. Sci Rep 12:8956. https://doi.org/10.1038/s41598-022-13152-x
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