The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review.

Journal: Journal of medical Internet research
Published Date: Jan 19, 2024

Abstract

BACKGROUND: Diabetes mellitus (DM) is a major health concern among children with the widespread adoption of advanced technologies. However, concerns are growing about the transparency, replicability, biasedness, and overall validity of artificial intelligence studies in medicine.

Authors

  • Zsombor Zrubka
    Health Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary; Corvinus Institue for Advanced Studies, Corvinus University of Budapest, Budapest, Hungary. Electronic address: zrubka.zsombor@uni-obuda.hu.
  • Gábor Kertész
    John von Neumann Faculty of Informatics, Óbuda University, Budapest, Hungary.
  • László Gulácsi
    Health Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary; Corvinus Institue for Advanced Studies, Corvinus University of Budapest, Budapest, Hungary.
  • János Czere
    Doctoral School of Innovation Management, Óbuda University, Budapest, Hungary.
  • Áron Hölgyesi
    HECON Health Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary.
  • Hossein Motahari Nezhad
    HECON Health Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary.
  • Amir Mosavi
    Faculty of Informatics, Technische Universität Dresden, Dresden, Germany.
  • Levente Kovács
    Physiological Controls Research Center, Research and Innovation Center of Óbuda University, Óbuda University, Budapest, Hungary. Electronic address: kovacs.levente@nik.uni-obuda.hu.
  • Atul J Butte
    Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA.
  • Márta Péntek
    Health Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary.

Keywords

External Resources

Popular Topics
Recent Journals