Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach

Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach

Background Acute kidney injury (AKI) and acute kidney disease (AKD) are prevalent among pediatric patients, both linked to increased mortality and extended hospital stays. Early detection of kidney injury is crucial for improving outcomes. This study presents a machine learning-based risk prediction...

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Bibliographic Details
Main Authors: Lingyu Xu, Siqi Jiang, Chenyu Li, Xue Gao, Chen Guan, Tianyang Li, Ningxin Zhang, Shuang Gao, Xinyuan Wang, Yanfei Wang, Lin Che, Yan Xu
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Renal Failure
Subjects:
Pediatric
acute kidney injury
acute kidney disease
machine learning
prediction model
renal function trajectory
Online Access:https://www.tandfonline.com/doi/10.1080/0886022X.2024.2438858
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