Machine learning and the nomogram as the accurate tools for predicting postoperative malnutrition risk in esophageal cancer patients

Machine learning and the nomogram as the accurate tools for predicting postoperative malnutrition risk in esophageal cancer patients

BackgroundPostoperative malnutrition is a prevalent complication following esophageal cancer surgery, significantly impairing clinical recovery and long-term prognosis. This study aimed to develop and validate predictive models using machine learning algorithms and a nomogram to estimate the risk of...

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Bibliographic Details
Main Authors: Zhenmeng Lin, Hao He, Mingfang Yan, Xiamei Chen, Hanshen Chen, Jianfang Ke
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Nutrition
Subjects:
esophageal cancer
postoperative malnutrition
machine learning
nomogram
surgery
Online Access:https://www.frontiersin.org/articles/10.3389/fnut.2025.1606470/full
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