In Clinical and experimental otorhinolaryngology
Objectives : To present an up-to-date survey of the use of artificial intelligence (AI) in the field of otorhinolaryngology, with respect to opportunities, research challenges, and research directions.
Methods : We searched PubMed, the Cochrane Central Register of Controlled Trials, Embase, and the Web of Science. We initially retrieved 458 articles; we excluded non-English publications and duplicates, which resulted in a total of 90 remaining studies. These 90 studies were divided into those analyzing medical images, voice, medical devices, and clinical diagnoses and treatments.
Results : Most studies (42.22%, 38/90) used AI for image-based analysis, followed by clinical diagnosis and treatments (24 studies); each of the remaining two subcategories included 14 studies.
Conclusion : Machine and deep learning have been extensively applied in the field of otorhinolaryngology. However, performance varies and research challenges remain.
Tama Bayu Adhi, Kim Do Hyun, Kim Gyuwon, Lee Seungchul, Kim Soo Whan
Artificial intelligence, deep learning, machine learning, otorhinolaryngology