Predicting Mortality Using Machine Learning Algorithms in Patients Who Require Renal Replacement Therapy in the Critical Care Unit

Predicting Mortality Using Machine Learning Algorithms in Patients Who Require Renal Replacement Therapy in the Critical Care Unit

Background: General severity of illness scores are not well calibrated to predict mortality among patients receiving renal replacement therapy (RRT) for acute kidney injury (AKI). We developed machine learning models to make mortality prediction and compared their performance to that of the Sequenti...

Full description

Bibliographic Details
Main Authors: Hsin-Hsiung Chang, Jung-Hsien Chiang, Chi-Shiang Wang, Ping-Fang Chiu, Khaled Abdel-Kader, Huiwen Chen, Edward D. Siew, Jonathan Yabes, Raghavan Murugan, Gilles Clermont, Paul M. Palevsky, Manisha Jhamb
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Journal of Clinical Medicine
Subjects:
machine learning algorithm
mortality
acute kidney injury
renal replacement therapy
Online Access:https://www.mdpi.com/2077-0383/11/18/5289

Internet

https://www.mdpi.com/2077-0383/11/18/5289

Similar Items