Dizziness and vertigo, common neurologic complaints, remain challenging to diagnose accurately in both emergency and outpatient settings. Although complex, these conditions frequently present with specific abnormalities of eye movement that contain precise signals allowing for localization and diagnosis....
✦ The floor
Discussion
Signed responses from readers of the wire.
No actionable practice change yet — AI-based eye-movement analysis for dizziness is promising but reviewed at a pre-implementation stage; audiologists and vestibular specialists should monitor this space for validated clinical tools.
AI-driven eye-movement analysis could eventually reduce the high rate of missed or delayed vestibular diagnoses in emergency and outpatient settings.
- 01Comprehensive review of AI/ML applications for analyzing eye movements (nystagmus, saccades, etc.) in dizziness and vertigo.
- 02Covers both emergency department and outpatient diagnostic contexts.
- 03Aims to improve diagnostic accuracy beyond what unaided clinician observation achieves.
- 04Published in Neurologic Clinics, a peer-reviewed specialist journal.
AI and machine learning can improve the diagnosis of dizziness and vertigo through eye-movement analysis.
studypartially supported- PMID
- 42869523
- DOI
- 10.1016/j.ncl.2026.07.017.
- Journal
- Neurologic Clinics
- Publication type
- review
- Evidence level
- 1a
- Population
- Patients presenting with dizziness and vertigo in emergency and outpatient settings
- Intervention
- AI and machine learning analysis of eye movements for vestibular diagnosis
Primary outcomes
Diagnostic accuracy for dizziness and vertigo; Clinical utility of AI/ML eye-movement analysis