Prediction of acute kidney injury risk after cardiac surgery: using a hybrid machine learning algorithm

Prediction of acute kidney injury risk after cardiac surgery: using a hybrid machine learning algorithm

Abstract Background Acute kidney injury (AKI) is a serious complication after cardiac surgery. We derived and internally validated a Machine Learning preoperative model to predict cardiac surgery-associated AKI of any severity and compared its performance with parametric statistical models. Methods...

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Bibliographic Details
Main Authors: Yelena Petrosyan, Thierry G. Mesana, Louise Y. Sun
Format: Article
Language:English
Published: BMC 2022-05-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Cardiac surgery-associated acute kidney injury
Machine Learning
Random Forests
Data mining
Predictive modeling
Online Access:https://doi.org/10.1186/s12911-022-01859-w

Internet

https://doi.org/10.1186/s12911-022-01859-w

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