{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T18:26:00Z","timestamp":1787250360294,"version":"build-2736575974"},"reference-count":58,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T00:00:00Z","timestamp":1772409600000},"content-version":"vor","delay-in-days":1,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Health Science Reports"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Aim<\/jats:title>\n                    <jats:p>As dental anomalies can significantly affect esthetic and function, early detection and diagnosis are crucial for treatment and minimizing potential negative effects. Artificial intelligence (AI) has emerged as a promising tool for the segmentation and detection of dental anomalies in number, morphology, size, position, and structure that may be missed by dentists. This study aimed to investigate the application of various AI models in dental anomaly detection and diagnosis, including supernumerary teeth, tarodontism, impaction, ectopic eruption, and molar\u2010incisor hypomineralization in both dental radiography and photography.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>A comprehensive literature search was conducted in PubMed\/Medline, Scopus, Web of Science, and Google Scholar for studies published from the initiate up to 2023 on AI applications in dental anomaly detection. Inclusion criteria encompassed recent AI models utilizing imaging modalities for identifying dental abnormalities, with full\u2010text availability in English. Studies lacking imaging\u2010based AI applications or methodological clarity were excluded.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results and Conclusion<\/jats:title>\n                    <jats:p>A total of 20 studies assessed various AI models for detecting dental anomalies in radiographic and photographic imaging. Deep learning models, particularly EfficientDet\u2010D3, nnU\u2010Net, and ResNeXt, demonstrated the highest accuracy for supernumerary teeth, ectopic eruption, and molar\u2010incisor hypomineralization, respectively, with most models achieving accuracy rates above 85%. These findings underscore AI's significant potential for automated dental anomaly detection; however, performance varied across different anomalies and imaging modalities, highlighting the need for further optimization. Given the complexity of simultaneous dental anomalies, future research should focus on developing multi\u2010class AI models capable of detecting multiple conditions concurrently and integrating clinical and radiographic data for improved diagnostic accuracy and treatment planning.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/hsr2.71969","type":"journal-article","created":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T20:58:33Z","timestamp":1773003513000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Application of Artificial Intelligence in Detecting Dental Anomalies: Current Models, Imaging Modalities, and Future Directions"],"prefix":"10.1002","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9015-7105","authenticated-orcid":false,"given":"Mobina Sadat","family":"Zarabadi","sequence":"first","affiliation":[{"name":"USERN Office Qazvin University of Medical Sciences Qazvin Iran"},{"name":"Network of Interdisciplinarity in Neonates and Infants (NINI), Universal Scientific Education and Research Network (USERN) Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7577-5562","authenticated-orcid":false,"given":"Zeynab","family":"Pirayesh","sequence":"additional","affiliation":[{"name":"Department of Orthodontics and Dentofacial Orthopedics School of Dentistry Zanjan University of Medical Sciences Zanjan Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2182-2970","authenticated-orcid":false,"given":"Shaghayegh","family":"Najary","sequence":"additional","affiliation":[{"name":"Network of Interdisciplinarity in Neonates and Infants (NINI), Universal Scientific Education and Research Network (USERN) Tehran Iran"},{"name":"School of Dentistry Shahid Beheshti University of Medical Sciences Tehran Iran"},{"name":"USERN Office Shahid Beheshti University of Medical Sciences Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alireza Jafarzade","family":"Ghadimi","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering Islamic Azad University Central Tehran Branch Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2763-3292","authenticated-orcid":false,"given":"Mohammad","family":"Behnaz","sequence":"additional","affiliation":[{"name":"USERN Office Shahid Beheshti University of Medical Sciences Tehran Iran"},{"name":"Dental Research Center, Research Institute of Dental Sciences, School of Dentistry Shahid Beheshti University of Medical Sciences Tehran Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,3,2]]},"reference":[{"issue":"9","key":"e_1_2_15_2_1","article-title":"Epithelial\u2013Mesenchymal Interactions in Tooth Development and the Significant Role of Growth Factors and Genes With Emphasis on Mesenchyme\u2013A Review","volume":"10","author":"Puthiyaveetil J. 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