Deep learning in acute vertigo diagnosis.

Journal: Journal of the neurological sciences
PMID:

Abstract

Recent advances in artificial intelligence are transforming healthcare and there are increasing efforts to apply these breakthroughs to the diagnosis of acute vertigo. Because the diagnosis of vertigo relies on the analysis of eye movements, there are several unique considerations that must be made when implementing deep learning approaches to vertigo. This review discusses the need for diagnostic aids for acute vertigo, the techniques used to preprocess eye movement data and adapt deep learning models to vertigo, and summarizes and analyzes all published models to date.

Authors

  • David Pw Rastall
    The Johns Hopkins University School of Medicine, Department of Neurology, Division of Neuro-Visual & Vestibular Disorders, USA. Electronic address: DRastal1@jhmi.edu.
  • Kemar Green
    The Johns Hopkins University School of Medicine, Department of Neurology, Division of Advanced Clinical Neurology, USA.