Machine learning-based predictive model for enteral nutrition-associated diarrhea in ICU patients and its nursing applications

Machine learning-based predictive model for enteral nutrition-associated diarrhea in ICU patients and its nursing applications

BackgroundEnteral Nutrition-Associated Diarrhea (ENAD) is a common complication in critically ill patients, significantly impacting clinical outcomes. Accurately predicting the risk of ENAD is crucial for early intervention and improving patient care.ObjectiveThis study aims to develop and validate...

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Bibliographic Details
Main Authors: Xiaoying Liao, Chunhua Li, Qunyan Liu, Wang Xia, Zhenglin Liu, Jiamao Zhu, Wei Hu, Qionghua Hong
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Nutrition
Subjects:
enteral nutrition-associated diarrhea
machine learning
random forest
feature importance
critically ill patients
Online Access:https://www.frontiersin.org/articles/10.3389/fnut.2025.1584717/full
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