Quality of information on YouTube about artificial intelligence in dental radiology

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dc.authorid0000-0002-6429-4197
dc.contributor.authorCesur Aydın, Kader
dc.contributor.authorGüneç, Hüseyin Gürkan
dc.date.accessioned2020-11-16T07:19:21Z
dc.date.available2020-11-16T07:19:21Z
dc.date.issued2020
dc.departmentİstanbul Medipol Üniversitesi, Diş Hekimliği Fakültesi, Ağız, Diş ve Çene Radyolojisi Ana Bilim Dalı
dc.description.abstractObjectives This study was designed to investigate Artificial Intelligence in Dental Radiology (AIDR) videos on YouTube in terms of popularity, content, reliability, and educational quality. Methods Two researchers systematically searched about AIDR on YouTube on January 27, 2020, by using the terms "artificial intelligence in dental radiology," "machine learning in dental radiology," and "deep learning in dental radiology." The search was performed in English, and 60 videos for each keyword were assessed. Video source, content type, time since upload, duration, and number of views, likes, and dislikes were recorded. Video popularity was reported using Video Power Index (VPI). The accuracy and reliability of the source of information were measured using the adapted DISCERN score. The quality of the videos was measured using JAMAS and modified Global Quality Score (mGQS) and content via Total Concent Evaluation (TCE). Results There was high interobserver agreement for DISCERN (intraclass correlation coefficient [ICC]: 0.975; 95% confidence interval [CI]: 0.957-0.985; P: 0.000;P < 0.05) and mGQS (ICC: 0.904; 95% CI: 0.841-0.943; P: 0.000;P < 0.05). Academic source videos had higher DISCERN, GQS, and TCE, revealing both reliability and quality. Also, positive relationship of VPI with mGQS (30.1%) (P: 0.035) and DISCERN (38.1%) (P: 0.007) is detected. The scores revealed 51.9% relationship between mGQS and DISCERN (P: 0.001); and educational quality predictor scores revealed 62.5% relationship between TCE and GQS (P: 0.000). Conclusion Despite the limited number of relevant videos, YouTube involves reliable and quality videos that can be used by dentists about learning AIDR.
dc.identifier.citationCesur Aydın, K. ve Güneç, H. G. (2020). Quality of information on YouTube about artificial intelligence in dental radiology. Journal of Dental Education, 84(10), 1166-1172. https://dx.doi.org/10.1002/jdd.12362
dc.identifier.doi10.1002/jdd.12362
dc.identifier.endpage1172
dc.identifier.issn0022-0337
dc.identifier.issn1930-7837
dc.identifier.issue10
dc.identifier.scopusqualityQ2
dc.identifier.startpage1166
dc.identifier.urihttps://dx.doi.org/10.1002/jdd.12362
dc.identifier.urihttps://hdl.handle.net/20.500.12511/6032
dc.identifier.volume84
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherWiley
dc.relation.ispartofJournal of Dental Educationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectArtificial Intelligence
dc.subjectDeep Learning
dc.subjectDental Radiology
dc.subjectInternet
dc.subjectYoutube
dc.titleQuality of information on YouTube about artificial intelligence in dental radiology
dc.typeArticle

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