Interpretable machine learning models for early prediction of acute kidney injury after cardiac surgery

Interpretable machine learning models for early prediction of acute kidney injury after cardiac surgery

Abstract Objective Postoperative acute kidney injury (PO-AKI) is a common complication after cardiac surgery. We aimed to evaluate whether machine learning algorithms could significantly improve the risk prediction of PO-AKI. Methods The retrospective cohort study included 2310 adult patients underg...

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Bibliographic Details
Main Authors: Jicheng Jiang, Xinyun Liu, Zhaoyun Cheng, Qianjin Liu, Wenlu Xing
Format: Article
Language:English
Published: BMC 2023-11-01
Series:BMC Nephrology
Subjects:
Acute kidney Injury
Cardiac surgery
Machine learning
Predictive model
Online Access:https://doi.org/10.1186/s12882-023-03324-w

Internet

https://doi.org/10.1186/s12882-023-03324-w

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