Separation of stroke from vestibular neuritis using the video head impulse test: machine learning models versus expert clinicians.

Background: Acute vestibular syndrome usually represents either vestibular neuritis (VN), an innocuous viral illness, or posterior circulation stroke (PCS), a potentially life-threatening event. The video head impulse test (VHIT) is a quantitative measure of the vestibulo-ocular reflex that can distinguish between these two diagnoses. It can be rapidly performed at the bedside by any trained healthcare professional but requires interpretation by an expert clinician.

Machine learning models help differentiate between causes of recurrent spontaneous vertigo.

Background: Vestibular migraine (VM) and Menière's disease (MD) are two common causes of recurrent spontaneous vertigo. Using history, video-nystagmography and audiovestibular tests, we developed machine learning models to separate these two disorders.

Methods: We recruited patients with VM or MD from a neurology outpatient facility.