{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T02:34:45Z","timestamp":1792204485930,"version":"4.4.0"},"reference-count":157,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T00:00:00Z","timestamp":1690761600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Esthet Restor Dent"],"published-print":{"date-parts":[[2023,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The applications of artificial intelligence (AI) are increasing in restorative dentistry; however, the AI performance is unclear for dental professionals. The purpose of this narrative review was to evaluate the applications, functions, and accuracy of AI in diverse aspects of restorative dentistry including caries detection, tooth preparation margin detection, tooth restoration design, metal structure casting, dental restoration\/implant detection, removable partial denture design, and tooth shade determination.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Overview<\/jats:title>\n                    <jats:p>An electronic search was performed on Medline\/PubMed, Embase, Web of Science, Cochrane, Scopus, and Google Scholar databases. English\u2010language articles, published from January 1, 2000, to March 1, 2022, relevant to the aforementioned aspects were selected using the key terms of artificial intelligence, machine learning, deep learning, artificial neural networks, convolutional neural networks, clustering, soft computing, automated planning, computational learning, computer vision, and automated reasoning as inclusion criteria. A manual search was also performed. Therefore, 157 articles were included, reviewed, and discussed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Based on the current literature, the AI models have shown promising performance in the mentioned aspects when being compared with traditional approaches in terms of accuracy; however, as these models are still in development, more studies are required to validate their accuracy and apply them to routine clinical practice.<\/jats:p>\n                    <jats:p>Clinical Significance: AI with its specific functions has shown successful applications with acceptable accuracy in diverse aspects of restorative dentistry. The understanding of these functions may lead to novel applications with optimal accuracy for AI in restorative dentistry.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jerd.13079","type":"journal-article","created":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T05:04:30Z","timestamp":1690779870000},"page":"842-859","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["Applications, functions, and accuracy of artificial intelligence in restorative dentistry: A literature review"],"prefix":"10.1111","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2394-6643","authenticated-orcid":false,"given":"Farhad","family":"Tabatabaian","sequence":"first","affiliation":[{"name":"Department of Oral Health Sciences, Faculty of Dentistry The University of British Columbia  Vancouver British Columbia Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siddharth 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