Interpretable machine learning model for early prediction of acute kidney injury in patients with rhabdomyolysis

Interpretable machine learning model for early prediction of acute kidney injury in patients with rhabdomyolysis

Abstract. Background. Rhabdomyolysis (RM) is a complex set of clinical syndromes. RM-induced acute kidney injury (AKI) is a common illness in war and military operations. This study aimed to develop an interpretable and generalizable model for early AKI prediction in patients with RM. Methods. Retro...

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Bibliographic Details
Main Authors: Ximu Zhang, Xiuting Liang, Zhangning Fu, Yibo Zhou, Yao Fang, MD, Xiaoli Liu, BS, Qian Yuan, Rui Liu, Quan Hong, Chao Liu
Format: Article
Language:English
Published: Wolters Kluwer Health/LWW 2024-12-01
Series:Emergency and Critical Care Medicine
Online Access:http://journals.lww.com/10.1097/EC9.0000000000000126
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