Machine learning for predicting all-cause mortality of metabolic dysfunction-associated fatty liver disease: a longitudinal study based on NHANES

Machine learning for predicting all-cause mortality of metabolic dysfunction-associated fatty liver disease: a longitudinal study based on NHANES

Abstract Background The mortality burden of metabolic dysfunction-associated fatty liver disease (MAFLD) is rising, making it crucial to predict mortality and identify the factors influencing it. While advanced machine learning algorithms are gaining recognition as effective tools for clinical predi...

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Bibliographic Details
Main Authors: Xueni Wang, Huihui Chen, Luqiao Wang, Wenguang Sun
Format: Article
Language:English
Published: BMC 2025-05-01
Series:BMC Gastroenterology
Subjects:
All-cause mortality
Machine learning
Metabolic dysfunction-associated fatty liver disease
Fatty liver
Online Access:https://doi.org/10.1186/s12876-025-03946-4
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https://doi.org/10.1186/s12876-025-03946-4

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