Artificial intelligence for understanding concussion: Retrospective cluster analysis on the balance and vestibular diagnostic data of concussion patients.

Journal: PloS one
PMID: 30939164

Abstract

OBJECTIVES: We propose a bottom-up, machine-learning approach, for the objective vestibular and balance diagnostic data of concussion patients, to provide insight into the differences in patients' phenotypes, independent of existing diagnoses (unsupervised learning).

Authors

  • Rosa M S Visscher
    Institute for Biomechanics, ETH Zurich, Zurich, Switzerland.
  • Nina Feddermann-Demont
    Department of Neurology, Interdisciplinary Center for Vertigo and Neurological Visual Disorders, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Fausto Romano
    Department of Neurology, Interdisciplinary Center for Vertigo and Neurological Visual Disorders, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Dominik Straumann
    Department of Neurology, Interdisciplinary Center for Vertigo and Neurological Visual Disorders, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Giovanni Bertolini
    Department of Neurology, Interdisciplinary Center for Vertigo and Neurological Visual Disorders, University Hospital Zurich, University of Zurich, Zurich, Switzerland.

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