Machine learning algorithm for predict the in-hospital mortality in critically ill patients with congestive heart failure combined with chronic kidney disease

Machine learning algorithm for predict the in-hospital mortality in critically ill patients with congestive heart failure combined with chronic kidney disease

Background The objective of this study was to develop and validate a machine learning (ML) model for predict in-hospital mortality among critically ill patients with congestive heart failure (CHF) combined with chronic kidney disease (CKD).Methods After employing least absolute shrinkage and selecti...

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Bibliographic Details
Main Authors: Xunliang Li, Zhijuan Wang, Wenman Zhao, Rui Shi, Yuyu Zhu, Haifeng Pan, Deguang Wang
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Renal Failure
Subjects:
Congestive heart failure
chronic kidney disease
machine learning
mortality
critically care
Online Access:https://www.tandfonline.com/doi/10.1080/0886022X.2024.2315298
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https://www.tandfonline.com/doi/10.1080/0886022X.2024.2315298

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