Machine learning algorithm to predict mortality in critically ill patients with sepsis-associated acute kidney injury

Machine learning algorithm to predict mortality in critically ill patients with sepsis-associated acute kidney injury

Abstract This study aimed to establish and validate a machine learning (ML) model for predicting in-hospital mortality in patients with sepsis-associated acute kidney injury (SA-AKI). This study collected data on SA-AKI patients from 2008 to 2019 using the Medical Information Mart for Intensive Care...

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Bibliographic Details
Main Authors: Xunliang Li, Ruijuan Wu, Wenman Zhao, Rui Shi, Yuyu Zhu, Zhijuan Wang, Haifeng Pan, Deguang Wang
Format: Article
Language:English
Published: Nature Portfolio 2023-03-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-32160-z

Internet

https://doi.org/10.1038/s41598-023-32160-z

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