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dc.contributor.authorDashti, Mahmood-
dc.contributor.authorLondono, Jimmy-
dc.contributor.authorGhasemi, Shohreh-
dc.contributor.authordkk.-
dc.date.accessioned2024-11-12T02:19:16Z-
dc.date.available2024-11-12T02:19:16Z-
dc.date.issued2024-
dc.identifier.issn1658-3612-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/7840-
dc.description.abstractObjectives: This research was aimed at assessing comprehension, attitudes, and perspectives regarding artificial intelligence (AI) in dentistry. The null hypothesis was a lack of foundational understanding of AI in dentistry. Methods: This systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted in May 2023. The eligibility criteria included cross-sectional studies published in English until July 2023, focusing solely on dentists or dental students. Data on AI knowledge, use, and perceptions were extracted and assessed for bias risk with the Joanna Briggs Institute checklist. Results: Of 408 publications, 22 relevant articles were identified, and 13 studies were included in the review. The average basic AI knowledge score was 58.62 % among dental students and 71.75%among dentists. More dental students (72.01 %) than dentists (62.60 %) believed in AI’s potential for advancing dentistry. Conclusions: Thorough AI instruction in dental schools and continuing education programs for practitioners are urgently needed to maximize AI’s potential benefits in dentistry. An integrated PhD program could drive revolutionary discoveries and improve patient care globally. Embracing AI with informed understanding and training will position dental professionals at the forefront of technological advancements in the field.en_US
dc.language.isoen_USen_US
dc.publisherJournal of Taibah University Medical Sciencesen_US
dc.relation.ispartofseriesReview Article;327-337-
dc.subjectArtificial intelligenceen_US
dc.subjectDeep learningen_US
dc.subjectDental practitioneren_US
dc.subjectDental studentsen_US
dc.subjectDentistryen_US
dc.subjectMachine learningen_US
dc.titleAttitudes, knowledge, and perceptions of dentists and dental students toward artificial intelligence: a systematic reviewen_US
dc.typeArticleen_US
Appears in Collections:Vol 19 No 2 (2024)

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