Predicting the risk of lean non-alcoholic fatty liver disease based on interpretable machine models in a Chinese T2DM population

Predicting the risk of lean non-alcoholic fatty liver disease based on interpretable machine models in a Chinese T2DM population

BackgroundNon-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, seriously threatening the public health. Although the proportion of patients with lean NAFLD is lower than that of patients with obese NALFD, it should not be overlooked. This study aimed to construct inter...

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Bibliographic Details
Main Authors: Shixue Bao, Qiankai Jin, Tieqiao Wang, Yushan Mao, Guoqing Huang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Endocrinology
Subjects:
lean non-alcoholic fatty liver disease
type 2 diabetes mellitus
interpretable machine learning
prediction model
predict risk
Online Access:https://www.frontiersin.org/articles/10.3389/fendo.2025.1626203/full
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