Classifying Type 2 Diabetes Using N-Glycan Profiling and Machine Learning Algorithms.

Journal: Studies in health technology and informatics
PMID: 40270390

Abstract

BACKGROUND: Type 2 diabetes (T2D) continues to present a global public health challenge due to its increasing prevalence. Early diagnosis is critical for preventing complications, but current screening methods often fail to detect early diabetic conditions.

Authors

  • Veronika Gombas
    Department of Computer Science and Systems Technology, University of Pannonia, Veszprem, Hungary.
  • Rebeka Torok
    Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Hungary.
  • Marta Vitai
    DRC Drug Research Center Ltd., H-8230 Balatonfured, Hungary.
  • Laszlo Koranyi
    DRC Drug Research Center Ltd., H-8230 Balatonfured, Hungary.
  • Gabor Jarvas
    Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Hungary.
  • Andras Guttman
    Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Hungary; Horváth Csaba Memorial Laboratory of Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary. Electronic address: guttmanandras@med.unideb.hu.
  • Agnes Vathy-Fogarassy
    Department of Computer Science and Systems Technology, University of Pannonia, Veszprem, Hungary.

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