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  11. Artificial Intelligence In Rhinology

Artificial Intelligence in Rhinology

Nuray Bayar Muluk1, Erdi Özdemir2, Ahmet Arslanoğlu2

  • 1Department of Otorhinolaryngology, Faculty of Medicine, Kirikkale University, Kirikkale.

The Journal of Craniofacial Surgery
|July 3, 2025

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View abstract on PubMed

Summary
This summary is machine-generated.

Artificial intelligence (AI) is transforming rhinology by improving diagnostics and surgical planning. Machine learning and deep learning algorithms offer enhanced decision-making and pave the way for future robotic sinonasal surgery.

Area of Science:

  • Otolaryngology
  • Medical Informatics
  • Computer Science

Background:

  • Artificial intelligence (AI) is increasingly integrated into various medical fields.
  • Rhinology, the study of the nose and its diseases, can benefit from advanced computational tools.

Purpose of the Study:

  • To review the current and emerging applications of artificial intelligence (AI) in rhinology.
  • To explore the potential impact of AI on diagnosis, surgical planning, and patient care in rhinology.

Main Methods:

  • A comprehensive literature search was performed using PubMed and Medline databases.
  • The search covered publications from the year 2000 to 2025, focusing on AI applications in rhinology.

Main Results:

  • Machine learning (ML) algorithms, including classification, are used for decision-making in rhinology.
Keywords:
Artificial intelligencepredicting stepsquantifying sinus volumesrhinology

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  • Deep learning (DL) aids in diagnosing sinusitis and quantifying sinus volumes from radiographic images.
  • AI advancements are enabling surgical phase assessment, complication prediction, and the development of robotic sinonasal surgery.

    • Conclusions:

    • AI enhances healthcare quality, reduces costs, and improves accessibility in rhinology.
    • AI applications can support diagnostic roles, even in underserved areas.
    • The integration of AI, ML, DL, and robotics promises to revolutionize rhinology practice.
    surgical phase assessment