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Benign Paroxysmal Positional Vertigo

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Update on benign paroxysmal positional vertigo.

Journal of neurology
Benign paroxysmal positional vertigo (BPPV) is the most common cause of vertigo worldwide. This review considers recent advances in the diagnosis and management of BPPV including the use of web-based technology and artificial intelligence as well as ...

Nystagmus patterns classification framework based on deep learning and optical flow.

Computers in biology and medicine
Benign paroxysmal positional vertigo (BPPV) is the most common vestibular peripheral vertigo disease characterized by brief recurrent vertigo with positional nystagmus. Clinically, it is common to recognize the patterns of nystagmus by analyzing infr...

Diagnosing the benign paroxysmal positional vertigo via 1D and deep-learning composite model.

Journal of neurology
BACKGROUND: Benign Paroxysmal Positional Vertigo (BPPV) is the leading cause of vertigo, and its characteristic nystagmus induced by positional maneuvers makes it a good model for Artificial Intelligence (AI) diagnosis. However, during the testing pr...

A nystagmus extraction system using artificial intelligence for video-nystagmography.

Scientific reports
Benign paroxysmal positional vertigo (BPPV), the most common vestibular disorder, is diagnosed by an examiner changing the posture of the examinee and inducing nystagmus. Among the diagnostic methods used to observe nystagmus, video-nystagmography ha...

BPPV Information on Google VersusĀ AI (ChatGPT).

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: To quantitatively compare online patient education materials found using traditional search engines (Google) versus conversational Artificial Intelligence (AI) models (ChatGPT) for benign paroxysmal positional vertigo (BPPV).

Multimodal deep learning-based diagnostic model for BPPV.

BMC medical informatics and decision making
BACKGROUND: Benign paroxysmal positional vertigo (BPPV) is a prevalent form of vertigo that necessitates a skilled physician to diagnose by observing the nystagmus and vertigo resulting from specific changes in the patient's position. In this study, ...

Deep Learning-Based Nystagmus Detection for BPPV Diagnosis.

Sensors (Basel, Switzerland)
In this study, we propose a deep learning-based nystagmus detection algorithm using video oculography (VOG) data to diagnose benign paroxysmal positional vertigo (BPPV). Various deep learning architectures were utilized to develop and evaluate nystag...