Quality of information on YouTube about artificial intelligence in dental radiology

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dc.contributor.authorAydin, Kader Cesur
dc.contributor.authorGunec, Huseyin Gurkan
dc.date.accessioned2024-03-13T10:30:39Z
dc.date.available2024-03-13T10:30:39Z
dc.date.issued2020
dc.departmentİstanbul Beykent Üniversitesien_US
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.en_US
dc.identifier.doi10.1002/jdd.12362
dc.identifier.endpage1172en_US
dc.identifier.issn0022-0337
dc.identifier.issn1930-7837
dc.identifier.issue10en_US
dc.identifier.pmid32813894en_US
dc.identifier.scopus2-s2.0-85089475892en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1166en_US
dc.identifier.urihttps://doi.org/10.1002/jdd.12362
dc.identifier.urihttps://hdl.handle.net/20.500.12662/3452
dc.identifier.volume84en_US
dc.identifier.wosWOS:000562916400001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofJournal Of Dental Educationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectartificial intelligenceen_US
dc.subjectdeep learningen_US
dc.subjectdental radiologyen_US
dc.subjectinterneten_US
dc.subjectYouTubeen_US
dc.titleQuality of information on YouTube about artificial intelligence in dental radiologyen_US
dc.typeArticleen_US

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