{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,30]],"date-time":"2026-05-30T03:24:50Z","timestamp":1780111490361,"version":"3.54.0"},"reference-count":20,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T00:00:00Z","timestamp":1667433600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Oral Rehabilitation"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Temporomandibular disorders (TMDs) are disabling conditions with a negative impact on the quality of life. Their diagnosis is a complex and multi\u2010factorial process that should be conducted by experienced professionals, and most TMDs remain often undetected. Increasing the awareness of un\u2010experienced dentists and supporting the early TMD recognition may help reduce this gap. Artificial intelligence (AI) allowing both to process natural language and to manage large knowledge bases could support the diagnostic process.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>In this work, we present the experience of an AI\u2010based system for supporting non\u2010expert dentists in early TMD recognition.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The system was based on commercially available AI services. The prototype development involved a preliminary domain analysis and relevant literature identification, the implementation of the core cognitive computing services, the web interface and preliminary testing. Performance evaluation included a retrospective review of seven available clinical cases, together with the involvement of expert professionals for usability testing.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The system comprises one module providing possible diagnoses according to a list of symptoms, and a second one represented by a question and answer tool, based on natural language. We found that, even when using commercial services, the training guided by experts is a key factor and that, despite the generally positive feedback, the application's best target is untrained professionals.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We provided a preliminary proof of concept of the feasibility of implementing an AI\u2010based system aimed to support non\u2010specialists in the early identification of TMDs, possibly allowing a faster and more frequent referral to second\u2010level medical centres. Our results showed that AI is a useful tool to improve TMD detection by facilitating a primary diagnosis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/joor.13383","type":"journal-article","created":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T03:59:35Z","timestamp":1666756775000},"page":"31-38","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Artificial intelligence to support early diagnosis of temporomandibular disorders: A preliminary case study"],"prefix":"10.1111","volume":"50","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7793-4552","authenticated-orcid":false,"given":"Bachar","family":"Reda","sequence":"first","affiliation":[{"name":"Dipartimento di Scienze Mediche, Chirurgiche e Della Salute University of Trieste  Trieste Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luca","family":"Contardo","sequence":"additional","affiliation":[{"name":"Dipartimento di Scienze Mediche, Chirurgiche e Della Salute University of Trieste  Trieste Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Prenassi","sequence":"additional","affiliation":[{"name":"Department of Engineering and Architecture University of Trieste  Trieste Italy"},{"name":"Centro Clinico per la Neurostimolazione, le Neurotecnologie ed i Disordini del Movimento, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico  Milan Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enrico","family":"Guerra","sequence":"additional","affiliation":[{"name":"Department of Engineering and Architecture University of Trieste  Trieste Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giacomo","family":"Derchi","sequence":"additional","affiliation":[{"name":"Department of Surgical Pathology, Medicine, Molecular and Critical Area University of Pisa  Pisa Italy"},{"name":"Tuscan Stomatologic Institute  Camaiore 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