Clinical evaluation of a machine learning-based dysphagia risk prediction tool.

Journal: European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PMID: 38743079

Abstract

PURPOSE: The rise of digitization promotes the development of screening and decision support tools. We sought to validate the results from a machine learning based dysphagia risk prediction tool with clinical evaluation.

Authors

  • Markus Gugatschka
    Department of Phoniatrics, ENT University Hospital Graz, Medical University Graz, Graz, Austria. markus.gugatschka@medunigraz.at.
  • Nina Maria Egger
    Department of Phoniatrics, ENT University Hospital Graz, Medical University Graz, Graz, Austria.
  • K Haspl
    Department of Phoniatrics, ENT University Hospital Graz, Medical University Graz, Graz, Austria.
  • David Hortobagyi
    Department of Phoniatrics, ENT University Hospital Graz, Medical University Graz, Graz, Austria.
  • Stefanie Jauk
    CBmed, Graz, Austria.
  • Marlies Feiner
    Division of Phoniatrics, Medical University Graz, Graz, Austria.
  • Diether Kramer
    Steiermärkische Krankenanstaltengesellschaft m.b.H. (KAGes), Graz, Austria.

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