Artificial Intelligence Applications in Otolaryngology: Current Status and Future Perspectives

Abstract

Otolaryngology is among the medical specialties most suitable for the application of artificial intelligence (AI), largely due to the wide variety of data generated in daily practice. Otoscopic and endoscopic images, voice recordings, audiological tests, vestibular assessments, computed tomography (CT), magnetic resonance imaging (MRI), and digital pathology slides provide rich sources of information that can be analyzed using AI-based methods. As a result, AI has emerged as a valuable tool for tasks such as image classification, segmentation, risk prediction, outcome estimation, and optimization of clinical workflows. Despite growing scientific interest, however, many AI studies in otolaryngology remain at the developmental stage and have not yet undergone sufficient clinical validation for routine use. Currently, the most practical applications of AI involve well-defined and repetitive clinical tasks. These include supporting newborn hearing screening programs, predicting cochlear implant outcomes, interpreting otoscopic and nasal endoscopic images, assisting vestibular assessments, analyzing voice recordings for laryngeal disorders, and improving risk stratification in head and neck oncology. In contrast, complex clinical decisions that require comprehensive patient evaluation continue to depend on physician expertise, with AI functioning primarily as a supportive technology rather than an independent decision-maker. The future role of AI in otolaryngology is therefore not to replace clinicians but to enhance decision-making by improving efficiency, consistency, and data utilization. Successful implementation will require not only high diagnostic accuracy but also careful attention to validation, data quality, patient privacy, regulatory oversight, and clinical accountability. Consequently, the major challenge ahead is not the development of new algorithms, but their safe and responsible integration into clinical practice.