Double-Weighted Bayesian Model Combination for Metabolomics Data Description and Prediction

Double-Weighted Bayesian Model Combination for Metabolomics Data Description and Prediction

Background/Objectives: This study presents a novel double-weighted Bayesian Ensemble Machine Learning (DW-EML) model aimed at improving the classification and prediction of metabolomics data. This discipline, which involves the comprehensive analysis of metabolites in a biological system, provides v...

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Bibliographic Details
Main Authors: Jacopo Troisi, Martina Lombardi, Alessio Trotta, Vera Abenante, Andrea Ingenito, Nicole Palmieri, Sean M. Richards, Steven J. K. Symes, Pierpaolo Cavallo
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Metabolites
Subjects:
metabolomics
ensemble machine learning
Bayesian model
precision medicine
diagnostic tools
Online Access:https://www.mdpi.com/2218-1989/15/4/214
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