Artificial Intelligence in Otology, Neurotology and Vestibular Medicine: Emerging Methods and Clinical Applications

Dear Colleagues,

Artificial intelligence (AI) and machine learning (ML) are rapidly transforming the fields of otology, neurotology and vestibular medicine, offering unprecedented opportunities to enhance diagnostic accuracy, streamline clinical decision-making, and optimize patient management. This Special Issue, titled "Artificial Intelligence in Otology, Neurotology and Vestibular Medicine: Emerging Methods and Clinical Applications," aims to gather original research articles, systematic reviews, and clinical studies addressing the integration of AI-based methodologies across the full spectrum of otological and neurotological practice. 

We welcome contributions spanning the entire clinical spectrum: from otological and hearing disorders to balance diseases, including applications in neuroscience, otoneuroradiology, and skull base pathology. 

Topics of interest include, but are not limited to:

• AI-assisted analysis of otoscopic images;
• AI-assisted imaging analysis for the diagnosis and assessment of hearing disorders;
• Radiomics applied to cerebellopontine angle tumours and petrous bone lesions;
• Deep learning approaches for cholesteatoma detection, classification and staging;
• AI-assisted and evidence-based treatment selection for patients with various forms of hearing impairment;
• Diagnostic algorithms and therapeutic decision-making in facial nerve disorders;
• AI models for BPPV diagnosis and guidance of canalith repositioning maneuvers;
• AI-based video head impulse test (vHIT) signal analysis;
• Machine learning approaches for the classification and differential diagnosis of vestibular disorders.

The aim is to compile a collection of at least 8 high-quality articles that will contribute to establishing evidence-based frameworks for AI adoption in these specialties. Submissions may report novel algorithms, clinical validation studies, multicenter datasets, or translational findings bridging computational methods and clinical care.

We look forward to receiving your contributions.

Dr. Pietro Canzi
Dr. Edoardo Covelli
Dr. Filippo Di Lella
Guest Editors

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