{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T01:05:42Z","timestamp":1793408742849,"version":"4.5.0"},"reference-count":94,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2023,8,18]],"date-time":"2023-08-18T00:00:00Z","timestamp":1692316800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Today, with rapid advances in technology, computer-based studies and Artificial Intelligence (AI) approaches are finding their place in every field, especially in the medical sector, where they attract great attention. The Temporomandibular Joint (TMJ) stands as the most intricate joint within the human body, and diseases related to this joint are quite common. In this paper, we reviewed studies that utilize AI-based algorithms and computer-aided programs for investigating TMJ and TMJ-related diseases. We conducted a literature search on Google Scholar, Web of Science, and PubMed without any time constraints and exclusively selected English articles. Moreover, we examined the references to papers directly related to the topic matter. As a consequence of the survey, a total of 66 articles within the defined scope were assessed. These selected papers were distributed across various areas, with 11 focusing on segmentation, 3 on Juvenile Idiopathic Arthritis (JIA), 10 on TMJ Osteoarthritis (OA), 21 on Temporomandibular Joint Disorders (TMD), 6 on decision support systems, 10 reviews, and 5 on sound studies. The observed trend indicates a growing interest in artificial intelligence algorithms, suggesting that the number of studies in this field will likely continue to expand in the future.<\/jats:p>","DOI":"10.3390\/diagnostics13162700","type":"journal-article","created":{"date-parts":[[2023,8,18]],"date-time":"2023-08-18T09:13:44Z","timestamp":1692350024000},"page":"2700","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["A Comprehensive Review of Artificial Intelligence Based Algorithms Regarding Temporomandibular Joint Related Diseases"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0531-4645","authenticated-orcid":false,"given":"Sifa","family":"Ozsari","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Ankara University, 06830 Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mehmet Serdar","family":"G\u00fczel","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Ankara University, 06830 Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dilek","family":"Y\u0131lmaz","sequence":"additional","affiliation":[{"name":"Faculty of Dentistry, Baskent University, 06490 Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4134-5756","authenticated-orcid":false,"given":"K\u0131van\u00e7","family":"Kamburo\u011flu","sequence":"additional","affiliation":[{"name":"Department of Dentomaxillofacial Radiology, Ankara University, 06560 Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"publisher","first-page":"1122","DOI":"10.1016\/j.cell.2018.02.010","article-title":"Identifying medical diagnoses and treatable diseases by image-based deep learning","volume":"172","author":"Kermany","year":"2018","journal-title":"Cell"},{"key":"ref_2","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1016\/j.eururo.2020.04.023","article-title":"Deep learning predicts molecular subtype of muscle-invasive bladder cancer from conventional histopathological slides","volume":"78","author":"Woerl","year":"2020","journal-title":"Eur. 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