{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T03:54:05Z","timestamp":1791172445308,"version":"4.1.0"},"reference-count":61,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["2025\/08148\u20104"],"award-info":[{"award-number":["2025\/08148\u20104"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Oral Pathology Medicine"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background\/Aims<\/jats:title>\n                    <jats:p>Risk prediction models (RPMs) based on histopathological analysis of oral epithelial dysplasia (OED) are increasingly used to stratify patients with oral potentially malignant disorders (OPMDs) and support personalized management. This systematic review and meta\u2010analysis evaluated artificial intelligence (AI)\u2010based models compared with conventional human microscopy for predicting malignant transformation (MT).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 32 studies published between 1998 and 2026 were included (9 AI\u2010based and 23 human\u2010based), focusing on OED in oral leukoplakia (OL), erythroleukoplakia, and erythroplakia. AI approaches addressed prediction or prognostic tasks using machine learning (ML), deep learning (DL), or hybrid methods, with multilayer perceptron and random forest among the most frequently used algorithms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Meta\u2010analysis demonstrated strong discriminative performance for AI models (pooled odds ratio [OR]\u2009=\u200912.64; 95% CI: 5.65\u201328.26;\n                      <jats:italic>I<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u200957%). Human evaluation also confirmed a significant association between OED and MT (OR\u2009=\u20093.42; 95% CI: 2.07\u20135.68), with substantial heterogeneity (\n                      <jats:italic>I<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u200985%). AI\u2010based models showed higher specificity and more consistent performance, while sensitivity remained comparable to human assessment.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Overall, AI\u2010based RPMs demonstrate promising and more reliable discriminative ability, primarily by improving decision precision rather than detection rates. However, further standardization, external validation, and larger multicentric datasets are required for clinical implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jop.70168","type":"journal-article","created":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T01:56:08Z","timestamp":1784858168000},"page":"1019-1033","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Malignant Transformation in Oral Epithelial Dysplasia: A Systematic Comparison of Artificial Intelligence\u2010Based Risk Models and Pathologist\u2010Based Microscopy"],"prefix":"10.1111","volume":"55","author":[{"given":"Diele Carine Barreto","family":"Arantes","sequence":"first","affiliation":[{"name":"Oral Medicine and Pathology, Faculdade S\u00e3o Leopoldo Mandic Research Institute, Rua Dr. Jos\u00e9 Rocha Junqueira  Campinas S\u00e3o Paulo Brazil"},{"name":"Modelo Clinic, Oral and Digestive Medicine  Belo Horizonte 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