{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T22:31:39Z","timestamp":1785191499646,"version":"3.55.0"},"reference-count":35,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T00:00:00Z","timestamp":1760054400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T00:00:00Z","timestamp":1760054400000},"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":["Int Endodontic J"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>This study evaluated the effect of a short, personalised training session on student performance in using an artificial intelligence (AI)\u2010based platform for pulp exposure prediction before caries excavation and determined the required sample size for a further randomised controlled trial (RCT).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methodology<\/jats:title>\n                    <jats:p>Undergraduate dental students were randomly assigned to the experimental (training) group and the control (no training) group. The training group received a 1\u2010h training session before undertaking the experiment, focusing on the uses, applications, and drawbacks of AI and carious lesion penetration depth. The theoretical presentation was followed by practical exercises and a quiz to check learning progress. Later, participants in both groups completed an experimental task involving 292 cases. They were asked to predict pulp exposure using an AI\u2010based website. Sample size calculations determined the required sample size, with 80% power and an alpha of 5%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>18 participants were enrolled (9 in each group). The agreement between participants' decisions and AI predictions regarding the presence or absence of pulp exposure (agreeableness with AI) was higher in the training group compared to the control group (0.83 vs. 0.76). The training group had a slightly higher mean F1\u2010score (0.63 vs. 0.62), accuracy (0.69 vs. 0.68), and sensitivity (0.63 vs. 0.59) than the control group. Based on the sample size calculation, at least 31 participants per group are needed for the future RCT.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The results support further investigation of customised training sessions prior to using an AI\u2010based platform to assess their impact on dental students' agreement with AI predictions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial Registration<\/jats:title>\n                    <jats:p>\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/clinicaltrial.gov\">ClinicalTrial.gov<\/jats:ext-link>\n                      identifier: NCT05912361\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/iej.70046","type":"journal-article","created":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:10:41Z","timestamp":1760159441000},"page":"1248-1256","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["The Impact of Training Dental Students to Use an Artificial Intelligence\u2013Based Platform for Pulp Exposure Prediction Prior to Deep Caries Excavation: A Proof\u2010of\u2010Concept Randomised Controlled Trial"],"prefix":"10.1111","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1012-0730","authenticated-orcid":false,"given":"Shaqayeq","family":"Ramezanzade","sequence":"first","affiliation":[{"name":"Department of Cariology and Endodontics, Section for Clinical Oral Microbiology, Faculty of Health and Medical Sciences, Department of Odontology University of Copenhagen  Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4942-1389","authenticated-orcid":false,"given":"Tudor Laurentiu","family":"Dascalu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Science University of Copenhagen  Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2974-1331","authenticated-orcid":false,"given":"Azam","family":"Bakhshandeh","sequence":"additional","affiliation":[{"name":"Department of Cariology and Endodontics, Section for Clinical Oral Microbiology, Faculty of Health and Medical Sciences, Department of Odontology University of Copenhagen  Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0684-2025","authenticated-orcid":false,"given":"Sergio E.","family":"Uribe","sequence":"additional","affiliation":[{"name":"Department of Conservative Dentistry and Oral Health Riga Stradins University  Riga Latvia"},{"name":"Baltic Biomaterials Centre of Excellence Headquarters at Riga Technical University &amp; RSU Institute of Stomatology  Riga Latvia"},{"name":"Department of Conservative Dentistry and Periodontology LMU University Hospital, LMU Munich  Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7739-7788","authenticated-orcid":false,"given":"Bulat","family":"Ibragimov","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Science University of Copenhagen  Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2183-6400","authenticated-orcid":false,"given":"Lars","family":"Bj\u00f8rndal","sequence":"additional","affiliation":[{"name":"Department of Cariology and Endodontics, Section for Clinical Oral Microbiology, Faculty of Health and Medical Sciences, Department of Odontology University of Copenhagen  Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,10,10]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"crossref","unstructured":"Agarwal N. A.Moehring P.Rajpurkar andT.Salz.2023.\u201cCombining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology.\u201dNBER Working Paper No. 31422. 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