Predicting metabolic dysfunction associated steatotic liver disease using explainable machine learning methods

Predicting metabolic dysfunction associated steatotic liver disease using explainable machine learning methods

Abstract Early and accurate identification of patients at high risk of metabolic dysfunction-associated steatotic liver disease (MASLD) is critical to prevent and improve prognosis potentially. We aimed to develop and validate an explainable prediction model based on machine learning (ML) approaches...

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Bibliographic Details
Main Authors: Yihao Yu, Yuqi Yang, Qian Li, Jing Yuan, Yan Zha
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Metabolic dysfunction-associated steatotic liver disease
Prediction model
Machine learning
SHAP
Online Access:https://doi.org/10.1038/s41598-025-96478-6
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https://doi.org/10.1038/s41598-025-96478-6

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