Ιnnovative applications of artificial intelligence in Rhinology
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Date
2026-02-09
Authors
Κουραμπί, Χαμίντα
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Abstract
Rhinology, a subspecialty of otolaryngology, has evolved significantly through technological advancements, with artificial intelligence (AI) emerging as a transformative force in modern practice. This narrative review critically examines the role of AI in enhancing diagnostic accuracy, refining surgical precision, and enabling personalized treatment strategies in rhinology.
A structured literature search was conducted in PubMed and Scopus databases covering the period 2010–2025. Following screening and eligibility assessment of 536 studies, just 23 studies were included in the qualitative synthesis.
AI applications, particularly convolutional neural networks, demonstrate exceptional performance in analyzing medical imaging, detecting nasal polyps, segmenting anatomical structures, and predicting patient outcomes. Despite these promising capabilities, challenges such as data standardization, model interpretability, and integration into clinical workflows remain barriers to widespread adoption. The review also explores future directions, including AI-driven surgical navigation, multimodal data integration, and predictive analytics, underscoring the potential of AI to redefine patient care through improved efficiency, objectivity, and personalization. Ultimately, AI represents a pivotal innovation poised to advance rhinology into a new era of data-driven and precision medicine, though its successful implementation will require ongoing validation, interdisciplinary collaboration, and ethical oversight.
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Keywords
Artificial intelligence, Rhinology, Medical imaging, Surgical navigation, Nasal polyps, Personalized medicine, Deep learning, Diagnostics, Prognostics, Clinical decision support