{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T13:53:19Z","timestamp":1792158799887,"version":"4.4.0"},"reference-count":31,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T00:00:00Z","timestamp":1635724800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100015311","name":"Novartis Institutes for BioMedical Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100015311","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Oral Diseases"],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>This study aimed to develop a diagnostic support tool using pretrained models for classifying panoramic images of the temporomandibular joint (TMJ) into normal and osteoarthritis (OA) cases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Subjects and Methods<\/jats:title>\n                    <jats:p>A total of 858 panoramic images of the TMJ (395 normal and 463\u00a0TMJ\u2010OA) were obtained from 518 individuals from January 2015 to December 2018. The data were randomly divided into training, validation, and testing sets (6:2:2). We used pretrained Resnet152 and EfficientNet\u2010B7 as transfer learning models. The accuracy, specificity, sensitivity, area under the curve, and gradient\u2010weighted class activation mapping (grad\u2010CAM) of both trained models were evaluated. The performances of the trained models were compared to that of dentists (both TMD specialists and general dentists).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The classification accuracies of ResNet\u2010152 and EfficientNet\u2010B7 were 0.87 and 0.88, respectively. The trained models exhibited the highest accuracy in OA classification. In the grad\u2010CAM analysis, the trained models focused on specific areas in osteoarthritis images where erosion or osteophyte were observed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The artificial intelligence model improved the diagnostic power of TMJ\u2010OA when trained with two\u2010dimensional panoramic condyle images and can be effectively applied by dentists as a screening diagnostic tool for TMJ\u2010OA.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/odi.14056","type":"journal-article","created":{"date-parts":[[2021,10,24]],"date-time":"2021-10-24T13:40:03Z","timestamp":1635082803000},"page":"1050-1059","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":62,"title":["Deep learning for osteoarthritis classification in temporomandibular joint"],"prefix":"10.1111","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8728-8013","authenticated-orcid":false,"given":"Won","family":"Jung","sequence":"first","affiliation":[{"name":"Department of Oral Medicine School of Dentistry Jeonbuk National University  Jeonju Korea"},{"name":"Research Institute of Clinical Medicine of Jeonbuk National University\u2010Biomedical Research and Institute of Jeonbuk National University Hospital  Jeonju South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8923-1478","authenticated-orcid":false,"given":"Kyung\u2010Eun","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Oral Medicine School of Dentistry Jeonbuk National University  Jeonju Korea"},{"name":"Research Institute of Clinical Medicine of Jeonbuk National University\u2010Biomedical Research and Institute of Jeonbuk National University Hospital  Jeonju South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1817-4645","authenticated-orcid":false,"given":"Bong\u2010Jik","family":"Suh","sequence":"additional","affiliation":[{"name":"Department of Oral Medicine School of Dentistry Jeonbuk National University  Jeonju Korea"},{"name":"Research Institute of Clinical Medicine of Jeonbuk National University\u2010Biomedical Research and Institute of Jeonbuk National University Hospital  Jeonju South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5278-3807","authenticated-orcid":false,"given":"Hyun","family":"Seok","sequence":"additional","affiliation":[{"name":"Research Institute of Clinical Medicine of Jeonbuk National University\u2010Biomedical Research and Institute of Jeonbuk National University Hospital  Jeonju South Korea"},{"name":"Department of Oral and Maxillofacial Surgery School of Dentistry Jeonbuk National University  Jeonju Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9942-2400","authenticated-orcid":false,"given":"Dae\u2010Woo","family":"Lee","sequence":"additional","affiliation":[{"name":"Research Institute of Clinical Medicine of Jeonbuk National University\u2010Biomedical Research and Institute of Jeonbuk National University Hospital  Jeonju South Korea"},{"name":"Department of Pediatric Dentistry School of Dentistry Jeonbuk National University  Jeonju Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,11]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tripleo.2009.02.023"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.oooo.2015.04.008"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1079\u20102104(97)90128\u20101"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2018.04.009"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/14651858.CD007261.pub2"},{"key":"e_1_2_10_7_1","first-page":"301","article-title":"Research diagnostic criteria for temporomandibular disorders: Review, criteria, examinations and specifications, critique","volume":"6","author":"Dworkin S. 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