{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T13:14:53Z","timestamp":1791983693138,"version":"4.4.0"},"reference-count":37,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T00:00:00Z","timestamp":1724889600000},"content-version":"vor","delay-in-days":28,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical &amp;amp; Exp Dental Res"],"published-print":{"date-parts":[[2024,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Aim<\/jats:title>\n                    <jats:p>Dental caries is largely preventable, yet an important global health issue. Numerous systematic reviews have summarized the efficacy of artificial intelligence (AI) models for the diagnosis and detection of dental caries. Therefore, this umbrella review aimed to synthesize the results of systematic reviews on the application and effectiveness of AI models in diagnosing and detecting dental caries.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>MEDLINE\/PubMed, IEEE Explore, Embase, and Cochrane Database of Systematic Reviews were searched to retrieve studies. Two authors independently screened the articles based on eligibility criteria and then, appraised the included articles. The findings are summarized in tabulation form and discussed using the narrative method.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Result<\/jats:title>\n                    <jats:p>A total of 1249 entries were identified out of which 7 were finally included. The most often employed AI algorithms were the multilayer perceptron, support vector machine (SVM), and neural networks. The algorithms were built to perform the segmentation, classification, caries detection, diagnosis, and caries prediction from several sources, including periapical radiographs, panoramic radiographs, smartphone images, bitewing radiographs, near\u2010infrared light transillumination images, and so forth. Convoluted neural networks (CNN) demonstrated high sensitivity, specificity, and area under the curve in the caries detection, segmentation, and classification tests. Notably, AI in conjunction with periapical and panoramic radiography images yielded better accuracy in detecting and diagnosing dental caries.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>AI models, especially convolutional neural network (CNN)\u2010based models, have an enormous amount of potential for accurate, objective dental caries diagnosis and detection. However, ethical considerations and cautious adoption remain critical to its successful integration into routine practice.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cre2.70004","type":"journal-article","created":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T05:14:24Z","timestamp":1724908464000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["Artificial Intelligence in Dental Caries Diagnosis and Detection: An Umbrella Review"],"prefix":"10.1002","volume":"10","author":[{"given":"Sapna","family":"Negi","sequence":"first","affiliation":[{"name":"Department of Dental Research Cell, Dr. D. Y. Patil Dental College and Hospital Dr. D. Y. Patil Vidyapeeth Pune Maharashtra India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ankita","family":"Mathur","sequence":"additional","affiliation":[{"name":"Department of Dental Research Cell, Dr. D. Y. Patil Dental College and Hospital Dr. D. Y. Patil Vidyapeeth Pune Maharashtra India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Snehasish","family":"Tripathy","sequence":"additional","affiliation":[{"name":"Department of Dental Research Cell, Dr. D. Y. Patil Dental College and Hospital Dr. D. Y. Patil Vidyapeeth Pune Maharashtra India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vini","family":"Mehta","sequence":"additional","affiliation":[{"name":"Department of Dental Research Cell, Dr. D. Y. Patil Dental College and Hospital Dr. D. Y. Patil Vidyapeeth Pune Maharashtra India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Niher Tabassum","family":"Snigdha","sequence":"additional","affiliation":[{"name":"Department of Dental Research, Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdul Habeeb","family":"Adil","sequence":"additional","affiliation":[{"name":"Department of Dental Research, Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0313-9695","authenticated-orcid":false,"given":"Mohmed Isaqali","family":"Karobari","sequence":"additional","affiliation":[{"name":"Department of Dental Research, Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India"},{"name":"Department of Restorative Dentistry &amp; Endodontics, Faculty of Dentistry University of Puthisastra Phnom Penh Cambodia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,8,29]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"crossref","unstructured":"Ahmed W. M. A. A.Azhari K. A.Fawaz et al.2023. \u201cArtificial Intelligence in the Detection and Classification of Dental Caries.\u201dJournal of Prosthetic Dentistry. Published ahead of print August 26 2023.https:\/\/doi.org\/10.1016\/j.prosdent.2023.07.013.","DOI":"10.1016\/j.prosdent.2023.07.013"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2020.110120"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.41694"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13020202"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.5195\/jmla.2018.345"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2018180850"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.2106\/JBJS.L.00597"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1093\/advances\/nmab150"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1177\/0022034515586763"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/odi.14516"},{"key":"e_1_2_11_12_1","unstructured":"JBI. n.d. \u201cCritical Appraisal Tools.\u201d Accessed January 1 2023.https:\/\/jbi.global\/critical-appraisal-tools."},{"key":"e_1_2_11_13_1","doi-asserted-by":"crossref","unstructured":"JBI.2020. \u201cChapter 10: Umbrella Reviews.\u201d InJBI Manual for Evidence Synthesis edited by E. 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