Machine Learning Techniques for Differential Diagnosis of Vertigo and Dizziness: A Review

Abstract

Vertigo is a sensation of movement that results from disorders of the inner ear balance organs and their central connections, with aetiologies that are often benign and sometimes serious. An individual who develops vertigo can be effectively treated only after a correct diagnosis of the underlying vestibular disorder is reached. Recent advances in artificial intelligence promise novel strategies for the diagnosis and treatment of patients with this common symptom. Human analysts may experience difficulties manually extracting patterns from large clinical datasets. Machine learning techniques can be used to visualize, understand, and classify clinical data to create a computerized, faster, and more accurate evaluation of vertiginous disorders. Practitioners can also use them as a teaching tool to gain knowledge and valuable insights from medical data. This paper provides a review of the literatures from 1999 to 2021 using various feature extraction and machine learning techniques to diagnose vertigo disorders. This paper aims to provide a better understanding of the work done thus far and to provide future directions for research into the use of machine learning in vertigo diagnosis.

Artificial intelligence for early stroke diagnosis in acute vestibular syndrome

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Automatic theranostics for long-term neurorehabilitation after stroke

“…As large amounts of data are generated during measurements for automated evaluation during self-help poststroke rehabilitation, machine learning (ML) methods have emerged as promising assistive techniques to healthcare providers who wish to rapidly analyze batches of data as well as project the neuro-behavioral metrics onto clinical assessment scores for readable results (Abraham et al, 2014 ; Kabade et al, 2021 ). Using the neuro-behavioral metrics and neuroimages as input features, the pretrained ML-based models can automatically distinguish differences between stroke patients and unimpaired participants.…”

Videooculography “HINTS” in Acute Vestibular Syndrome: A Prospective Study

“…Furthermore, intensive educational courses for ED physicians through vertigo experts are an option. Application of artificial intelligence on big patient's data in the future can lead to development of an accurate automated interpretation of VOG results ( 12 , 24 , 28 ).…”