{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T14:41:59Z","timestamp":1792248119847,"version":"4.4.0"},"reference-count":49,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Oral Diseases"],"published-print":{"date-parts":[[2024,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>This systematic review aimed at evaluating the performance of artificial intelligence (AI) models in detecting dental caries on oral photographs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Methodological characteristics and performance metrics of clinical studies reporting on deep learning and other machine learning algorithms were assessed. The risk of bias was evaluated using the quality assessment of diagnostic accuracy studies 2 (QUADAS\u20102) tool. A systematic search was conducted in EMBASE, Medline, and Scopus.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Out of 3410 identified records, 19 studies were included with six and seven studies having low risk of biases and applicability concerns for all the domains, respectively. Metrics varied widely and were assessed on multiple levels. F1\u2010scores for classification and detection tasks were 68.3%\u201394.3% and 42.8%\u201395.4%, respectively. Irrespective of the task, F1\u2010scores were 68.3%\u201395.4% for professional cameras, 78.8%\u201387.6%, for intraoral cameras, and 42.8%\u201380% for smartphone cameras. Limited studies allowed assessing AI performance for lesions of different severity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Automatic detection of dental caries using AI may provide objective verification of clinicians' diagnoses and facilitate patient\u2010clinician communication and teledentistry. Future studies should consider more robust study designs, employ comparable and standardized metrics, and focus on the severity of caries lesions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/odi.14659","type":"journal-article","created":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T14:38:23Z","timestamp":1688222303000},"page":"1765-1783","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":91,"title":["Detecting dental caries on oral photographs using artificial intelligence: A systematic review"],"prefix":"10.1111","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4364-7969","authenticated-orcid":false,"given":"Mohammad","family":"Moharrami","sequence":"first","affiliation":[{"name":"Faculty of Dentistry University of Toronto  Toronto Ontario Canada"},{"name":"Topic Group Dental Diagnostics and Digital Dentistry, ITU\/WHO Focus Group AI on Health  Geneva Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julie","family":"Farmer","sequence":"additional","affiliation":[{"name":"Faculty of Dentistry University of Toronto  Toronto Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sonica","family":"Singhal","sequence":"additional","affiliation":[{"name":"Faculty of Dentistry University of Toronto  Toronto Ontario Canada"},{"name":"Health Promotion, Chronic Disease and Injury Prevention Department Public Health Ontario  Toronto Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2096-7732","authenticated-orcid":false,"given":"Erin","family":"Watson","sequence":"additional","affiliation":[{"name":"Faculty of Dentistry University of Toronto  Toronto Ontario Canada"},{"name":"Department of Dental Oncology, Princess Margaret Cancer Centre  Toronto Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Glogauer","sequence":"additional","affiliation":[{"name":"Faculty of Dentistry University of Toronto  Toronto Ontario Canada"},{"name":"Department of Dental Oncology, Princess Margaret Cancer Centre  Toronto Ontario Canada"},{"name":"Department of Dentistry, Centre for Advanced Dental Research and Care Mount Sinai Hospital  Toronto Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8735-3014","authenticated-orcid":false,"given":"Alistair E W","family":"Johnson","sequence":"additional","affiliation":[{"name":"Program in Child Health Evaluative Sciences The Hospital for Sick Children  Toronto Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Falk","family":"Schwendicke","sequence":"additional","affiliation":[{"name":"Topic Group Dental Diagnostics and Digital Dentistry, ITU\/WHO Focus Group AI on Health  Geneva Switzerland"},{"name":"Oral Diagnostics, Digital Health and Health Services Research Charit\u00e9\u00a0\u2013 Universit\u00e4tsmedizin Berlin  Berlin Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlos","family":"Quinonez","sequence":"additional","affiliation":[{"name":"Faculty of Dentistry University of Toronto  Toronto Ontario Canada"},{"name":"Schulich School of Medicine and Dentistry Western University  London Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,7]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jdent.2021.103615"},{"key":"e_1_2_10_3_1","first-page":"119","article-title":"A computer\u2010aided automated methodology for the detection and classification of occlusal caries from photographic color images","volume":"62","author":"Berdouses E. 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