Tama Bayu Adhi, Kim Do Hyun, Kim Gyuwon, Kim Soo Whan, Lee Seungchul
Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, Korea.
Department of Otolaryngology-Head and Neck Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Clin Exp Otorhinolaryngol. 2020 Nov;13(4):326-339. doi: 10.21053/ceo.2020.00654. Epub 2020 Jun 18.
This study presents an up-to-date survey of the use of artificial intelligence (AI) in the field of otorhinolaryngology, considering opportunities, research challenges, and research directions. We searched PubMed, the Cochrane Central Register of Controlled Trials, Embase, and the Web of Science. We initially retrieved 458 articles. The exclusion of non-English publications and duplicates yielded a total of 90 remaining studies. These 90 studies were divided into those analyzing medical images, voice, medical devices, and clinical diagnoses and treatments. Most studies (42.2%, 38/90) used AI for image-based analysis, followed by clinical diagnoses and treatments (24 studies). Each of the remaining two subcategories included 14 studies. Machine learning and deep learning have been extensively applied in the field of otorhinolaryngology. However, the performance of AI models varies and research challenges remain.
本研究对人工智能(AI)在耳鼻咽喉科领域的应用进行了最新调查,探讨了其机遇、研究挑战和研究方向。我们检索了PubMed、Cochrane对照试验中央注册库、Embase和科学网。最初检索到458篇文章。排除非英文出版物和重复文章后,共剩下90项研究。这90项研究分为分析医学图像、语音、医疗设备以及临床诊断和治疗的研究。大多数研究(42.2%,38/90)将AI用于基于图像的分析,其次是临床诊断和治疗(24项研究)。其余两个子类别各有14项研究。机器学习和深度学习已在耳鼻咽喉科领域得到广泛应用。然而,AI模型的性能各不相同,研究挑战依然存在。