Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery

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dc.contributor.authorTama, Bayu Adhiko
dc.contributor.authorKim, Hyunko
dc.contributor.authorKim, Gyuwonko
dc.contributor.authorKim, Soo Whanko
dc.contributor.authorLee, Seungchulko
dc.date.accessioned2023-09-13T03:01:23Z-
dc.date.available2023-09-13T03:01:23Z-
dc.date.created2023-09-13-
dc.date.created2023-09-13-
dc.date.issued2020-11-
dc.identifier.citationCLINICAL AND EXPERIMENTAL OTORHINOLARYNGOLOGY, v.13, no.4, pp.326 - 339-
dc.identifier.issn1976-8710-
dc.identifier.urihttp://hdl.handle.net/10203/312553-
dc.description.abstractThis 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.languageEnglish-
dc.publisherKOREAN SOC OTORHINOLARYNGOL-
dc.titleRecent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery-
dc.typeArticle-
dc.identifier.wosid000587452600006-
dc.identifier.scopusid2-s2.0-85095695307-
dc.type.rimsART-
dc.citation.volume13-
dc.citation.issue4-
dc.citation.beginningpage326-
dc.citation.endingpage339-
dc.citation.publicationnameCLINICAL AND EXPERIMENTAL OTORHINOLARYNGOLOGY-
dc.identifier.doi10.21053/ceo.2020.00654-
dc.identifier.kciidART002647840-
dc.contributor.localauthorLee, Seungchul-
dc.contributor.nonIdAuthorTama, Bayu Adhi-
dc.contributor.nonIdAuthorKim, Hyun-
dc.contributor.nonIdAuthorKim, Gyuwon-
dc.contributor.nonIdAuthorKim, Soo Whan-
dc.description.isOpenAccessN-
dc.type.journalArticleReview-
dc.subject.keywordAuthorArtificial Intelligence-
dc.subject.keywordAuthorMachine Learning-
dc.subject.keywordAuthorDeep Learning-
dc.subject.keywordAuthorOtorhinolaryngology-
dc.subject.keywordPlusSQUAMOUS-CELL CARCINOMA-
dc.subject.keywordPlusCT TEXTURE ANALYSIS-
dc.subject.keywordPlusCOCHLEAR-IMPLANT-
dc.subject.keywordPlusCHRONIC RHINOSINUSITIS-
dc.subject.keywordPlusNEURAL-NETWORKS-
dc.subject.keywordPlusFORMULATION PARAMETERS-
dc.subject.keywordPlusSPEECH-INTELLIGIBILITY-
dc.subject.keywordPlusPREDICTION-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordPlusIDENTIFICATION-
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