Outcome prediction for acute kidney injury among hospitalized children via eXtreme Gradient Boosting algorithm

Acute kidney injury (AKI) is common among hospitalized children and is associated with a poor prognosis. The study sought to develop machine learning-based models for predicting adverse outcomes among hospitalized AKI children. We performed a retrospective study of hospitalized AKI patients aged 1 m...

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Bibliographic Details
Published in:	Scientific reports Vol. 12; no. 1; pp. 8956 - 11
Main Authors:	Deng, Ying-Hao, Luo, Xiao-Qin, Yan, Ping, Zhang, Ning-Ya, Liu, Yu, Duan, Shao-Bin
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 27.05.2022 Nature Publishing Group Nature Portfolio
Subjects:	631/114/1305 692/308/3187 692/308/409 692/4022/1585/2762 692/4022/1585/4 692/699/1585/2762 692/699/1585/4 692/700/1720/3187 692/700/1750 Acute Kidney Injury - diagnosis Acute Kidney Injury - etiology Acute Kidney Injury - therapy Algorithms Child Child, Hospitalized Children Dialysis Hospitalization Humanities and Social Sciences Humans Kidneys Learning algorithms Machine Learning multidisciplinary Patients Pediatrics Prediction models Prognosis Regression analysis Renal function Retrospective Studies Science Science (multidisciplinary)
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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