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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Autori principali:	Lingyu Xu, Siqi Jiang, Chenyu Li, Xue Gao, Chen Guan, Tianyang Li, Ningxin Zhang, Shuang Gao, Xinyuan Wang, Yanfei Wang, Lin Che, Yan Xu
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Taylor & Francis Group 2024-12-01
Serie:	Renal Failure
Soggetti:	Pediatric acute kidney injury acute kidney disease machine learning prediction model renal function trajectory
Accesso online:	https://www.tandfonline.com/doi/10.1080/0886022X.2024.2438858
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