# Artificial intelligence-driven clinical auxiliary diagnosis of benign paroxysmal positional vertigo

## TL;DR

This paper reviews how artificial intelligence can help diagnose a common type of dizziness called benign paroxysmal positional vertigo more accurately and objectively.

## Contribution

The paper systematically reviews AI's role in improving the diagnosis of BPPV and highlights its potential for future clinical applications.

## Key findings

- AI technologies can enhance the accuracy of BPPV diagnosis by analyzing nystagmus patterns.
- Current AI applications reduce subjectivity and improve diagnostic efficiency in BPPV.
- Future AI developments may enable personalized treatment strategies for BPPV patients.

## Abstract

Benign paroxysmal positional vertigo (BPPV) is one of the most prevalent peripheral vertigo disorders in clinical practice. Its definitive diagnosis relies heavily on characteristic nystagmus induced by positional provocative tests, which imposes high requirements on clinicians and is subject to limitations such as strong subjectivity. The breakthrough advances in artificial intelligence (AI) technologies have provided innovative solutions for the accurate diagnosis and personalized treatment of BPPV. This review systematically summarizes the research progress of AI in the clinical application of BPPV, its enormous potential to improve BPPV diagnostic efficacy, and future directions for development.