A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein

A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein

Abstract Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk of heart disease, stroke, and diabetes. Timely detection and intervention are crucial in preventing severe health outcomes. In this study, we implemented a machine learning (ML)-based predict...

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Main Authors: Bahareh Behkamal, Fatemeh Asgharian Rezae, Amin Mansoori, Rana Kolahi Ahari, Sobhan Mahmoudi Shamsabad, Mohammad Reza Esmaeilian, Gordon Ferns, Mohammad Reza Saberi, Habibollah Esmaily, Majid Ghayour-Mobarhan
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Metabolic syndrome
Liver function tests
High-sensitivity C-reactive protein (hs-CRP)
Machine learning
Online Access:https://doi.org/10.1038/s41598-025-06723-1
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