Machine learning of plasma metabolome identifies biomarker panels for metabolic syndrome: findings from the China Suboptimal Health Cohort
Metabolome
Angiology
Biomarker Discovery
DOI:
10.1186/s12933-022-01716-0
Publication Date:
2022-12-23T17:19:03Z
AUTHORS (7)
ABSTRACT
Metabolic syndrome (MetS) has been proposed as a clinically identifiable high-risk state for the prediction and prevention of cardiovascular diseases type 2 diabetes mellitus. As promising "omics" technology, metabolomics provides an innovative strategy to gain deeper understanding pathophysiology MetS. The study aimed systematically investigate metabolic alterations in MetS identify biomarker panels identification using machine learning methods.
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