Akademik Veri Yönetim Sistemi
Turkish Journal of Ear Nose and Throat, cilt.35, sa.1, ss.47-58, 2025 (Scopus)
Vertigo and dizziness symptoms affect approximately 20% of the population. With the increasing use of artificial intelligence (AI) in healthcare, AI applications have been developed to assess "vertigo and dizziness." A common approach in evaluating patients with these symptoms is to analyse the vestibule-ocular reflex (VOR). A review of the literature shows that data such as nystagmus evaluations, vestibular test results, and patient history are processed through AI methods-particularly deep learning models —to analyse data from patients experiencing dizziness. This study reviews current AI applications and outcomes in the field of vertigo and dizziness. The goal is to provide a summary of the studies and offer guidance for future research on the use of machine learning and AI in vertigo diagnosis. The applications being developed will streamline the differentiation between the central and peripheral causes of vestibular symptoms in high-demand areas such as neurology and otorhinolaryngology emergency departments. These advancements will enable more accurate and timely referrals and simplify vestibular assessments in audiology, otorhinolaryngology, and neurology clinics.