{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T11:08:26Z","timestamp":1789470506463,"version":"build-2803163510"},"reference-count":29,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T00:00:00Z","timestamp":1765756800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T00:00:00Z","timestamp":1765756800000},"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":["Journal of Dental Education"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>\n                      This pilot study evaluated the use of\n                      <jats:italic>Second Opinion<\/jats:italic>\n                      , an artificial intelligence (AI)\u2010based radiographic evaluation tool, to support instruction in radiographic caries detection by examining its impact on instructor diagnostic performance and inter\u2010instructor agreement, as well as its potential to improve instructional consistency.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study used data from faculty calibration and examination development for a second\u2010year predoctoral dental student instructional module on radiographic caries detection. Instructor diagnostic performance\u2014including sensitivity, specificity, accuracy, precision, and F1 score\u2014was evaluated with and without AI\u2010assisted interpretation across varying carious lesion depths.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Instructors demonstrated high baseline diagnostic performance, with group average metrics exceeding 91% across all parameters. There was strong agreement between\n                      <jats:italic>Second Opinion<\/jats:italic>\n                      and instructor assessments, and AI\u2010assisted interpretation led to modest, non\u2010significant improvements in diagnostic performance. Notably, AI use increased the rate of unanimous agreement, particularly for sound surfaces (E0) and early\u2010to\u2010moderate dentinal caries (D1\/D2).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      <jats:italic>Second Opinion<\/jats:italic>\n                      demonstrated diagnostic performance comparable to that of the instructor group in radiographic caries detection and contributed to improved inter\u2010instructor agreement. These findings support its use in instructor calibration and case selection, highlighting the potential of AI\u2010assisted interpretation to enhance instructional consistency and strengthen assessment reliability in dental radiographic education.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jdd.70126","type":"journal-article","created":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T06:00:53Z","timestamp":1765864853000},"page":"1342-1349","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Artificial Intelligence in Dental Education: A Pilot Study of Caries Detection Accuracy and Instructor Agreement"],"prefix":"10.1002","volume":"90","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-4127-6373","authenticated-orcid":false,"given":"Somyung","family":"Ji","sequence":"first","affiliation":[{"name":"Section of Oral and Maxillofacial Radiology UCLA School of Dentistry  Los Angeles California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ladan","family":"Daly","sequence":"additional","affiliation":[{"name":"Department of Clinical Oral Healthcare University of the Pacific, Arthur A. Dugoni School of Dentistry  San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kumar","family":"Shah","sequence":"additional","affiliation":[{"name":"Section of Prosthodontics UCLA School of Dentistry  Los Angeles California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5435-7046","authenticated-orcid":false,"given":"Vinodh","family":"Bhoopathi","sequence":"additional","affiliation":[{"name":"Section of Public and Population Health UCLA School of Dentistry  Los Angeles California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2244-9939","authenticated-orcid":false,"given":"Sanjay M.","family":"Mallya","sequence":"additional","affiliation":[{"name":"Section of Oral and Maxillofacial Radiology UCLA School of Dentistry  Los Angeles California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,12,15]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"Commission on Dental Accreditation \u201cAccreditation Standards for Dental Education Programs \u201d2025 https:\/\/coda.ada.org\/\u2010\/media\/project\/ada\u2010organization\/ada\/coda\/files\/predoc_standards.pdf."},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1080\/13562511003620001"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1259\/dmfr.20220279"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.identj.2023.11.006"},{"key":"e_1_2_9_6_1","volume-title":"Dental Education at the Crossroads: Challenges and Change","author":"Field M. 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