Machine learning for the prediction of acute kidney injury in patients with sepsis

Machine learning for the prediction of acute kidney injury in patients with sepsis

Abstract Background Acute kidney injury (AKI) is the most common and serious complication of sepsis, accompanied by high mortality and disease burden. The early prediction of AKI is critical for timely intervention and ultimately improves prognosis. This study aims to establish and validate predicti...

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Bibliographic Details
Main Authors: Suru Yue, Shasha Li, Xueying Huang, Jie Liu, Xuefei Hou, Yumei Zhao, Dongdong Niu, Yufeng Wang, Wenkai Tan, Jiayuan Wu
Format: Article
Language:English
Published: BMC 2022-05-01
Series:Journal of Translational Medicine
Subjects:
Acute kidney injury
Sepsis
Machine learning
Prediction model
MIMIC- III database
Online Access:https://doi.org/10.1186/s12967-022-03364-0

Internet

https://doi.org/10.1186/s12967-022-03364-0

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