# Current insights on predicting vestibular diseases using machine learning

## TL;DR

This paper reviews how machine learning can help predict and diagnose vestibular disorders, which affect balance and posture.

## Contribution

The paper provides a comprehensive review of current insights and applications of machine learning in predicting vestibular diseases.

## Key findings

- Machine learning can identify patterns in complex vestibular data to improve diagnosis.
- ML offers potential for early detection and personalized treatment of vestibular disorders.

## Abstract

The vestibular system is one of the three main systems responsible for maintaining balance and posture. Accurate vestibular inputs enable the perception of the head’s position and movement in space, and ensure coordination between head movements, eye movements, balance, and posture. Any dysfunction in the peripheral vestibular end organs, the vestibular nerve, or the central vestibular system may lead to vertigo, dizziness, and gait disturbances in individuals. Some syndromes that cause vertigo symptoms can be life threatening. Although peripheral vestibular pathologies are generally benign, they can reduce patients’ quality of life, cause falls, and hinder independence. Therefore, the diagnosis and management of vestibular disorders are of great importance. However, due to the complex structure of the vestibular system and the complexity of its symptoms, some vestibular diseases may go undiagnosed or be misdiagnosed. Machine learning (ML), a subfield of artificial intelligence, enables computer systems to learn patterns and relationships from data and make predictions or decisions. The growing capabilities of ML in data processing combined with the needs of healthcare, offer significant opportunities in early diagnosis of diseases, treatment planning, and personalization of healthcare services. The present review provides a general overview of the prediction of vestibular disorders using ML.