{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T06:48:27Z","timestamp":1791874107779,"version":"4.3.4"},"reference-count":9,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T00:00:00Z","timestamp":1791763200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T00:00:00Z","timestamp":1791763200000},"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":["European J Oral Sciences"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Artificial intelligence (AI) is increasingly influencing dental diagnosis and clinical decision\u2010making, yet many AI systems continue to represent disease and treatment outcomes through discrete categories. Although binary classification has contributed substantially to diagnostic performance, it does not always reflect how clinicians reason in practice. Dental decisions are frequently made under incomplete information, biological variability, and competing clinical findings, requiring dentists to weigh probabilities, alternative explanations, and degrees of confidence rather than simply choosing between two outcomes. This short communication argues that future dental AI should better represent this inherent clinical uncertainty. Fuzzy logic provides one possible conceptual framework, allowing partial membership and graded states rather than forcing complex biological conditions into rigid categories. Its potential value in dentistry extends beyond computation: it may help AI communicate uncertainty in ways that are more consistent with clinical reasoning. Such systems could provide graded diagnostic confidence, competing possibilities, or degrees of treatment suitability, rather than presenting apparently definitive answers. This approach may also support explainability and reduce inappropriate reliance on algorithmic recommendations. The future of dental AI may therefore depend not only on improving predictive accuracy, but also on representing the grey zones in which much of clinical dentistry takes place.<\/jats:p>","DOI":"10.1111\/eos.70155","type":"journal-article","created":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T06:07:43Z","timestamp":1791871663000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Beyond binary dentistry: Should artificial intelligence think more like clinicians?"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4250-9951","authenticated-orcid":false,"given":"Mohammed","family":"Turky","sequence":"first","affiliation":[{"name":"Department of Endodontics, Faculty of Dentistry Minia University  Minia Egypt"},{"name":"Department of Endodontics, Faculty of Dentistry Sphinx University  Assiut Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0726-7467","authenticated-orcid":false,"given":"Paul M. H.","family":"Dummer","sequence":"additional","affiliation":[{"name":"School of Dentistry, College of Biomedical and Life Sciences Cardiff University  Cardiff UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,10,12]]},"reference":[{"key":"e_1_2_1_5_2_1","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/j.identj.2025.02.005","article-title":"The transformative role of artificial intelligence in dentistry: a comprehensive overview. Part 1: fundamentals of AI, and its contemporary applications in dentistry","volume":"75","author":"Samaranayake L","year":"2025","journal-title":"Int Dent J"},{"key":"e_1_2_1_5_3_1","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.identj.2025.02.006","article-title":"The transformative role of artificial intelligence in dentistry: a comprehensive overview. Part 2: the promise and perils, and the international dental federation communique","volume":"75","author":"Tuygunov N","year":"2025","journal-title":"Int Dent J"},{"key":"e_1_2_1_5_4_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.identj.2025.109336","article-title":"Integrating AI into dentistry: technical pathways and clinical applications in oral diseases\u2013a comprehensive overview","volume":"76","author":"Yuan Y","year":"2026","journal-title":"Int Dent J"},{"key":"e_1_2_1_5_5_1","article-title":"Determinants of clinical decision making under uncertainty in dentistry: a scoping review","volume":"13","author":"Murdoch AIK","year":"2023","journal-title":"Diagnostics (Basel, Switzerland)"},{"key":"e_1_2_1_5_6_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrai.2025.100030","article-title":"Evaluation metrics in medical imaging AI: Fundamentals, pitfalls, misapplications, and recommendations","volume":"3","author":"Kocak B","year":"2025","journal-title":"Eur J Radiol Artif Intell"},{"key":"e_1_2_1_5_7_1","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1038\/s41415-021-2726-4","article-title":"Dentistry\u2014art or science? Has the clinical freedom of the dental professional been undermined by guidelines, authoritative guidance and expert opinion?","volume":"230","author":"Caplin RL","year":"2021","journal-title":"Br Dent J"},{"key":"e_1_2_1_5_8_1","doi-asserted-by":"crossref","first-page":"802","DOI":"10.1093\/qjmed\/hcaf114","article-title":"Artificial intelligence for clinical reasoning: the reliability challenge and path to evidence\u2010based practice","volume":"118","author":"Xu H","year":"2025","journal-title":"QJM"},{"key":"e_1_2_1_5_9_1","unstructured":"GrM. Fuzzy Sets Fuzzy Logic and Their Applications.2020.https:\/\/doi.org\/10.3390\/books978\u20103\u201003928\u2010521\u20101"},{"key":"e_1_2_1_5_10_1","first-page":"1","article-title":"Dismantling binary opposition in fraud detection: a fuzzy deep learning framework for imbalanced transaction data","volume":"14","author":"Essa RM","year":"2026","journal-title":"Risks"}],"container-title":["European Journal of Oral Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/eos.70155","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/eos.70155","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/eos.70155","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T06:07:45Z","timestamp":1791871665000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/eos.70155"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,12]]},"references-count":9,"alternative-id":["10.1111\/eos.70155"],"URL":"https:\/\/doi.org\/10.1111\/eos.70155","archive":["Portico"],"relation":{},"ISSN":["0909-8836","1600-0722"],"issn-type":[{"value":"0909-8836","type":"print"},{"value":"1600-0722","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,12]]},"assertion":[{"value":"2026-09-24","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-30","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-10-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70155"}}