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Emerging paradigms, including self\u2010supervised learning for leveraging unlabelled data and explainable AI (XAI) techniques for model interpretability, are also discussed. Model evaluation relies on cross\u2010validation, hyperparameter optimisation, and performance metrics such as AUC, accuracy, sensitivity, specificity, and F1\u2010score.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Multiple studies demonstrate that AI\u2010based classifiers, especially random forest models built on salivary or tissue\u2010derived microbial features, achieve outstanding discrimination between OSCC patients and healthy controls in retrospective, single\u2010centre cohorts, with reported AUC values exceeding 0.99 and accuracy &gt;95%. However, these exceptional metrics should be interpreted with caution, as they are susceptible to cohort size, sampling site heterogeneity, batch effects, feature\u2010selection bias, and the absence of independent external validation. Beyond binary diagnosis, AI has been successfully applied to predict lymph node metastasis, explore tumour metabolic reprogramming, and assess environmental interactions. Integrated multi\u2010omics approaches further enhance the specificity and clinical relevance of microbial biomarkers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The convergence of AI and oral microbiome analysis is reshaping the diagnostic and therapeutic landscape of OSCC, and explore microbiome\u2010targeted combination therapies. Addressing these challenges will be pivotal to realising truly intelligent, personalised management and ultimately improving outcomes for OSCC patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ctm2.70723","type":"journal-article","created":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T06:40:31Z","timestamp":1783320031000},"source":"Crossref","is-referenced-by-count":0,"title":["Artificial intelligence and oral microbiome: Reshaping the diagnostic and therapeutic paradigm of OSCC"],"prefix":"10.1002","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4985-6147","authenticated-orcid":false,"given":"Rui","family":"Shi","sequence":"first","affiliation":[{"name":"Department of Oral and Maxillofacial Reconstruction the Affiliated Hospital of Qingdao University  Qingdao China"},{"name":"School of Stomatology, Qingdao University  Qingdao China"},{"name":"Department of Oral and Maxillofacial Surgery the Affiliated Hospital of Qingdao University  Qingdao 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