Predicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm – a 10-year multicenter retrospective study
BackgroundGastroparesis following complete mesocolic excision (CME) can precipitate a cascade of severe complications, which may significantly hinder postoperative recovery and diminish the patient’s quality of life. In the present study, four advanced machine learning algorithms—Extreme Gradient Bo...
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Main Authors: | Yuan Liu, Songyun Zhao, Wenyi Du, Wei Shen, Ning Zhou |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-01-01
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Series: | Frontiers in Medicine |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2024.1467565/full |
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