The Evolution and Application of Artificial Intelligence in Rhinology: A State of the Art Review

Ameen Amanian, Austin Heffernan, Masaru Ishii, Francis X. Creighton, Andrew Thamboo

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: To provide a comprehensive overview on the applications of artificial intelligence (AI) in rhinology, highlight its limitations, and propose strategies for its integration into surgical practice. Data Sources: Medline, Embase, CENTRAL, Ei Compendex, IEEE, and Web of Science. Review Methods: English studies from inception until January 2022 and those focusing on any application of AI in rhinology were included. Study selection was independently performed by 2 authors; discrepancies were resolved by the senior author. Studies were categorized by rhinology theme, and data collection comprised type of AI utilized, sample size, and outcomes, including accuracy and precision among others. Conclusions: An overall 5435 articles were identified. Following abstract and title screening, 130 articles underwent full-text review, and 59 articles were selected for analysis. Eleven studies were from the gray literature. Articles were stratified into image processing, segmentation, and diagnostics (n = 27); rhinosinusitis classification (n = 14); treatment and disease outcome prediction (n = 8); optimizing surgical navigation and phase assessment (n = 3); robotic surgery (n = 2); olfactory dysfunction (n = 2); and diagnosis of allergic rhinitis (n = 3). Most AI studies were published from 2016 onward (n = 45). Implications for Practice: This state of the art review aimed to highlight the increasing applications of AI in rhinology. Next steps will entail multidisciplinary collaboration to ensure data integrity, ongoing validation of AI algorithms, and integration into clinical practice. Future research should be tailored at the interplay of AI with robotics and surgical education.

Original languageEnglish (US)
Pages (from-to)21-30
Number of pages10
JournalOtolaryngology - Head and Neck Surgery (United States)
Volume169
Issue number1
DOIs
StatePublished - Jul 2023

Keywords

  • artificial intelligence
  • computer vision
  • machine learning
  • prediction
  • prognosis
  • rhinology

ASJC Scopus subject areas

  • Surgery
  • Otorhinolaryngology

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