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

Fatma Hilal YagınFahaid Al-HashemIrshad A AhmadFuzail AhmadAbedalrhman Alkhateeb
Published in: Nutrients (2024)
ML integrated with bioinformatics techniques offers accurate and positive T2D candidate biomarker discovery. The XGBoost model can successfully distinguish T2D based on metabolites.
Keyphrases
  • type diabetes
  • machine learning
  • small molecule
  • high throughput
  • ms ms
  • glycemic control
  • cardiovascular disease
  • high resolution
  • insulin resistance
  • big data
  • adipose tissue
  • deep learning
  • skeletal muscle
  • data analysis