Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery.

Journal: Nutrients
Published Date: May 20, 2024

Abstract

BACKGROUND: This study aims to identify unique metabolomics biomarkers associated with Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based machine learning (ML) algorithms integrated with bioinformatics techniques.

Authors

  • Fatma Hilal Yagin
    Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, Malatya, Türkiye.
  • Fahaid Al-Hashem
    Department of Physiology, College of Medicine, King Khalid University, Abha, Saudi Arabia.
  • Irshad Ahmad
    Department of Medical Rehabilitation Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia.
  • Fuzail Ahmad
    Respiratory Care Department, College of Applied Sciences, Almareefa University, Riyadh, Saudi Arabia.
  • Abedalrhman Alkhateeb
    School of Computer Science, University of Windsor, 401 Sunset Ave, Windsor, N9B 3P4, ON, Canada. alkhate@uwindsor.ca.

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