Development and validation of an interpretable 3 day intensive care unit readmission prediction model using explainable boosting machines

Development and validation of an interpretable 3 day intensive care unit readmission prediction model using explainable boosting machines

BackgroundIntensive care unit (ICU) readmissions are associated with mortality and poor outcomes. To improve discharge decisions, machine learning (ML) could help to identify patients at risk of ICU readmission. However, as many models are black boxes, dangerous properties may remain unnoticed. Wide...

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Bibliographic Details
Main Authors: Stefan Hegselmann, Christian Ertmer, Thomas Volkert, Antje Gottschalk, Martin Dugas, Julian Varghese
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Medicine
Subjects:
intensive care unit
readmission
artificial intelligence
machine learning
explainable AI
interpretable machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2022.960296/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2022.960296/full

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