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

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.

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Publication Details

Journal
Frontiers in Neurology
Published
2026-02-17
DOI
https://doi.org/10.3389/fneur.2026.1774729
Primary Topic
Vestibular and auditory disorders
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Siyang Dai, Yelin Wu, Ping Zhong, Xiaocui Kang
Frontiers in Neurology
Vestibular and auditory disorders
article

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

Siyang Dai, Yelin Wu, Ping Zhong, Xiaocui Kang
article en

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.

Frontiers in NeurologyVol. 17
University of Shanghai for Science and Technology (CN)
Openalex Percentile: Top 61%
Vestibular and auditory disorders
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