Machine Learning-Based Non-Invasive Prediction of Metabolic Dysfunction-Associated Steatohepatitis in Obese Patients: A Retrospective Study

Machine Learning-Based Non-Invasive Prediction of Metabolic Dysfunction-Associated Steatohepatitis in Obese Patients: A Retrospective Study

<b>Objectives</b>: We aimed to develop and validate machine learning (ML) models that integrate clinical and laboratory data for the non-invasive prediction of metabolic dysfunction-associated steatohepatitis (MASH) in an obese population. <b>Methods</b>: In this retrospectiv...

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Bibliographic Details
Main Authors: Jie Chen, Bo Zhang, Yong Cheng, Yuanchen Jia, Biao Zhou
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Diagnostics
Subjects:
metabolic dysfunction-associated steatohepatitis (MASH)
metabolic dysfunction-associated fatty liver disease (MAFLD)
machine learning
non-invasive diagnosis
Online Access:https://www.mdpi.com/2075-4418/15/9/1096
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