DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tama, Bayu Adhi | ko |
dc.contributor.author | Kim, Hyun | ko |
dc.contributor.author | Kim, Gyuwon | ko |
dc.contributor.author | Kim, Soo Whan | ko |
dc.contributor.author | Lee, Seungchul | ko |
dc.date.accessioned | 2023-09-13T03:01:23Z | - |
dc.date.available | 2023-09-13T03:01:23Z | - |
dc.date.created | 2023-09-13 | - |
dc.date.created | 2023-09-13 | - |
dc.date.issued | 2020-11 | - |
dc.identifier.citation | CLINICAL AND EXPERIMENTAL OTORHINOLARYNGOLOGY, v.13, no.4, pp.326 - 339 | - |
dc.identifier.issn | 1976-8710 | - |
dc.identifier.uri | http://hdl.handle.net/10203/312553 | - |
dc.description.abstract | 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. | - |
dc.language | English | - |
dc.publisher | KOREAN SOC OTORHINOLARYNGOL | - |
dc.title | Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery | - |
dc.type | Article | - |
dc.identifier.wosid | 000587452600006 | - |
dc.identifier.scopusid | 2-s2.0-85095695307 | - |
dc.type.rims | ART | - |
dc.citation.volume | 13 | - |
dc.citation.issue | 4 | - |
dc.citation.beginningpage | 326 | - |
dc.citation.endingpage | 339 | - |
dc.citation.publicationname | CLINICAL AND EXPERIMENTAL OTORHINOLARYNGOLOGY | - |
dc.identifier.doi | 10.21053/ceo.2020.00654 | - |
dc.identifier.kciid | ART002647840 | - |
dc.contributor.localauthor | Lee, Seungchul | - |
dc.contributor.nonIdAuthor | Tama, Bayu Adhi | - |
dc.contributor.nonIdAuthor | Kim, Hyun | - |
dc.contributor.nonIdAuthor | Kim, Gyuwon | - |
dc.contributor.nonIdAuthor | Kim, Soo Whan | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Review | - |
dc.subject.keywordAuthor | Artificial Intelligence | - |
dc.subject.keywordAuthor | Machine Learning | - |
dc.subject.keywordAuthor | Deep Learning | - |
dc.subject.keywordAuthor | Otorhinolaryngology | - |
dc.subject.keywordPlus | SQUAMOUS-CELL CARCINOMA | - |
dc.subject.keywordPlus | CT TEXTURE ANALYSIS | - |
dc.subject.keywordPlus | COCHLEAR-IMPLANT | - |
dc.subject.keywordPlus | CHRONIC RHINOSINUSITIS | - |
dc.subject.keywordPlus | NEURAL-NETWORKS | - |
dc.subject.keywordPlus | FORMULATION PARAMETERS | - |
dc.subject.keywordPlus | SPEECH-INTELLIGIBILITY | - |
dc.subject.keywordPlus | PREDICTION | - |
dc.subject.keywordPlus | SYSTEM | - |
dc.subject.keywordPlus | IDENTIFICATION | - |
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