Current insights on predicting vestibular diseases using machine learning


Creative Commons License

Söylemez E., Şeker M. M.

Turkish Journal of Medical Sciences, cilt.55, sa.5, ss.1077-1087, 2025 (SCI-Expanded, Scopus, TRDizin) identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 55 Sayı: 5
  • Basım Tarihi: 2025
  • Doi Numarası: 10.55730/1300-0144.6062
  • Dergi Adı: Turkish Journal of Medical Sciences
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, MEDLINE, Veterinary Science Database, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.1077-1087
  • Anahtar Kelimeler: BPPV, Machine learning, Ménière’s disease, vestibular diseases, vestibular neuritis
  • Ankara Üniversitesi Adresli: Evet

Özet

The vestibular system is one of the three main systems responsible for maintaining balance and posture. Accurate vestibular inputs enable the perception of the head’s position and movement in space, and ensure coordination between head movements, eye movements, balance, and posture. Any dysfunction in the peripheral vestibular end organs, the vestibular nerve, or the central vestibular system may lead to vertigo, dizziness, and gait disturbances in individuals. Some syndromes that cause vertigo symptoms can be life threatening. Although peripheral vestibular pathologies are generally benign, they can reduce patients’ quality of life, cause falls, and hinder independence. Therefore, the diagnosis and management of vestibular disorders are of great importance. However, due to the complex structure of the vestibular system and the complexity of its symptoms, some vestibular diseases may go undiagnosed or be misdiagnosed. Machine learning (ML), a subfield of artificial intelligence, enables computer systems to learn patterns and relationships from data and make predictions or decisions. The growing capabilities of ML in data processing combined with the needs of healthcare, offer significant opportunities in early diagnosis of diseases, treatment planning, and personalization of healthcare services. The present review provides a general overview of the prediction of vestibular disorders using ML.