{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T19:03:34Z","timestamp":1790449414460,"version":"4.1.0"},"reference-count":25,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T00:00:00Z","timestamp":1726617600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004329","name":"Javna Agencija za Raziskovalno Dejavnost RS","doi-asserted-by":"publisher","award":["P2\u20100232"],"award-info":[{"award-number":["P2\u20100232"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"Javna Agencija za Raziskovalno Dejavnost RS","doi-asserted-by":"publisher","award":["J2\u20103059"],"award-info":[{"award-number":["J2\u20103059"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Forensic Sciences"],"published-print":{"date-parts":[[2024,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Age estimation plays a crucial role in various fields, including forensic science and anthropology. This study aims to develop and validate DentAge, a deep\u2010learning model for automated age prediction using panoramic dental X\u2010ray images. DentAge was trained on a dataset comprising 21,007 panoramic dental X\u2010ray images sourced from a private dental center in Slovenia. The dataset included subjects aged 4 to 97\u2009years with various dental conditions. Transfer learning was employed, initializing the model with ImageNet weights and fine\u2010tuning on the dental image dataset. The model was trained using stochastic gradient descent with momentum, and mean absolute error (MAE) served as the objective function. Across the test dataset, DentAge achieved an MAE of 3.12\u2009years, demonstrating its efficacy in age prediction. Notably, the model performed well across different age groups, with MAEs ranging from 1.94 (age group [10\u201320]) to 13.40\u2009years (age group [90\u2013100]). Visual evaluation revealed factors contributing to prediction errors, including prosthetic restorations, tooth loss, and bone resorption. DentAge represents a significant advancement in automated age prediction within dentistry. The model's robust performance across diverse age groups and dental conditions underscores its potential utility in real\u2010world scenarios. Our model will be accessible to the public for further adjustments and validation, ensuring DentAge's effectiveness and trustworthiness in practical scenarios.<\/jats:p>","DOI":"10.1111\/1556-4029.15629","type":"journal-article","created":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T23:19:46Z","timestamp":1726701586000},"page":"2069-2074","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["<scp>DentAge<\/scp>\n                    : Deep learning for automated age prediction using panoramic dental X\u2010ray images"],"prefix":"10.1111","volume":"69","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2607-5994","authenticated-orcid":false,"given":"\u017diga","family":"Bizjak","sequence":"first","affiliation":[{"name":"Laboratory of Imaging Technologies, Faculty of Electrical Engineering University of Ljubljana  Ljubljana Slovenia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tina","family":"Robi\u010d","sequence":"additional","affiliation":[{"name":"Zobozdravstvo Diamant  Celje Slovenia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,9,18]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.legalmed.2009.09.001"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1520\/JFS13455J"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/1556\u20104029.14182"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521\u2010019\u201004449\u20106"},{"key":"e_1_2_7_6_1","first-page":"42","article-title":"An automated technique to stage lower third molar development on panoramic radiographs for age estimation: a pilot study","volume":"35","author":"De Tobel J","year":"2017","journal-title":"J Forensic Odontostomatol"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2018.2869606"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2968765"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0251388"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00414\u2010020\u201002459\u2010x"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11548\u2010021\u201002474\u20102"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116038"},{"key":"e_1_2_7_13_1","first-page":"25","volume-title":"Proceedings of the 10th international symposium on image and signal processing and analysis; 2017 Sept 18\u201320; Ljublijana, Slovenia","author":"\u010cular L","year":"2017"},{"key":"e_1_2_7_14_1","first-page":"186","volume-title":"Bildverarbeitung f\u00fcr die Medizin 2021 [proceedings, German workshop on medical image computing]; 2021 Mar 7\u20139; Regensburg, Germany","author":"Wallraff S","year":"2021"},{"key":"e_1_2_7_15_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010023\u201048960\u20102"},{"key":"e_1_2_7_16_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12859\u2010022\u201004935\u20100"},{"key":"e_1_2_7_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00414\u2010023\u201002960\u2010z"},{"key":"e_1_2_7_18_1","doi-asserted-by":"publisher","DOI":"10.3390\/computation11020018"},{"key":"e_1_2_7_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_2_7_20_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2006.18.7.1527"},{"key":"e_1_2_7_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521\u2010019\u201004097\u2010w"},{"key":"e_1_2_7_22_1","doi-asserted-by":"publisher","DOI":"10.1259\/dmfr.20170362"},{"key":"e_1_2_7_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.forsciint.2017.08.032"},{"key":"e_1_2_7_24_1","doi-asserted-by":"publisher","DOI":"10.1520\/JFS2003259"},{"key":"e_1_2_7_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/0379\u20100738(95)01760\u2010G"},{"key":"e_1_2_7_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/0030\u20104220(68)90165\u20105"}],"container-title":["Journal of Forensic Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/1556-4029.15629","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T08:43:51Z","timestamp":1730450631000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/1556-4029.15629"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,18]]},"references-count":25,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["10.1111\/1556-4029.15629"],"URL":"https:\/\/doi.org\/10.1111\/1556-4029.15629","archive":["Portico"],"relation":{},"ISSN":["0022-1198","1556-4029"],"issn-type":[{"value":"0022-1198","type":"print"},{"value":"1556-4029","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,18]]},"assertion":[{"value":"2024-06-23","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-09-03","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-09-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}