Artificial Intelligence, Radiomics and Pathomics in Oral Cancer: A bibliometric analysis of Dimensions Database

Artificial Intelligence, Radiomics, and Pathomics in Oral Cancer: A bibliometric analysis of Dimensions Database | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Artificial Intelligence, Radiomics, and Pathomics in Oral Cancer: A bibliometric analysis of Dimensions Database Kabir Khatiwada, Krishala Khadka, Ekata Shah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7893373/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Background As one of the top five cancers in South and Southeast Asia, oral cancer continues to pose a serious threat to global health. Although traditional diagnostic techniques are frequently resource-intensive and unavailable in low-resource settings, early detection significantly improves results. Recently, pathomics, radiomics, and artificial intelligence (AI) have become revolutionary technologies in this area. Objective This bibliometric analysis aimed to map the research landscape and identify trends, influential authors, countries, and thematic hotspots in the application of AI, radiomics, and pathomics to oral cancer. Methods A comprehensive search of the Dimensions database was conducted on September 1, 2025, covering literature from 2015 to 2025. A total of 370 open-access English-language papers met the inclusion criteria. Bibliometric and visualization analyses were performed using Biblioshiny, VOSviewer, and Microsoft Excel. Results Publications on this topic have grown at an annual rate of 60.01%, with contributions from 36 countries and 1,802 authors. India (24.3%) and China (14.9%) were the leading contributors. “Scientific Reports” published the most papers (n = 22), while “Cancers” had the highest H-index (12). The most cited paper was by Almangush et al. (2020) with 305 citations. Keyword analysis revealed four major research clusters focusing on AI-based classification, AI-assisted prognosis prediction/treatment planning, diagnostic performance evaluation, and image segmentation. Conclusion Research on oral cancer is changing due to the combination of AI, radiomics, and pathomics, with a focus on precision treatment, prognostic modeling, and early diagnosis. Nonetheless, issues with algorithm transparency, data quality, and ethical governance persist. Oncology Artificial Intelligence and Machine Learning Artificial intelligence Radiomics Pathomics Oral cancer Bibliometric analysis Full Text Additional Declarations The authors declare no competing interests. Supplementary Files BiblioshinyReport202510181.xlsx Report from biblioshiny DimensionsPublication20250901122052.xlsx Included papers supplementaryfiguresandcharts.docx Additional/supplementary charts Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7893373","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":533060478,"identity":"ffa4832b-4958-475a-906a-3df7905b3a9e","order_by":0,"name":"Kabir 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Database\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Artificial intelligence, Radiomics, Pathomics, Oral cancer, Bibliometric analysis","lastPublishedDoi":"10.21203/rs.3.rs-7893373/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7893373/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAs one of the top five cancers in South and Southeast Asia, oral cancer continues to pose a serious threat to global health. Although traditional diagnostic techniques are frequently resource-intensive and unavailable in low-resource settings, early detection significantly improves results. Recently, pathomics, radiomics, and artificial intelligence (AI) have become revolutionary technologies in this area.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThis bibliometric analysis aimed to map the research landscape and identify trends, influential authors, countries, and thematic hotspots in the application of AI, radiomics, and pathomics to oral cancer.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA comprehensive search of the Dimensions database was conducted on September 1, 2025, covering literature from 2015 to 2025. A total of 370 open-access English-language papers met the inclusion criteria. Bibliometric and visualization analyses were performed using Biblioshiny, VOSviewer, and Microsoft Excel.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePublications on this topic have grown at an annual rate of 60.01%, with contributions from 36 countries and 1,802 authors. India (24.3%) and China (14.9%) were the leading contributors. \u0026ldquo;Scientific Reports\u0026rdquo; published the most papers (n\u0026thinsp;=\u0026thinsp;22), while \u0026ldquo;Cancers\u0026rdquo; had the highest H-index (12). The most cited paper was by Almangush et al. (2020) with 305 citations. Keyword analysis revealed four major research clusters focusing on AI-based classification, AI-assisted prognosis prediction/treatment planning, diagnostic performance evaluation, and image segmentation.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eResearch on oral cancer is changing due to the combination of AI, radiomics, and pathomics, with a focus on precision treatment, prognostic modeling, and early diagnosis. Nonetheless, issues with algorithm transparency, data quality, and ethical governance persist.\u003c/p\u003e","manuscriptTitle":"Artificial Intelligence, Radiomics, and Pathomics in Oral Cancer: A bibliometric analysis of Dimensions Database","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2025-11-13 19:31:52","doi":"10.21203/rs.3.rs-7893373/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2025-10-21 23:46:21","doi":"10.21203/rs.3.rs-7893373/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"53e60746-7d10-4683-8b2a-84dba075d6a9","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57382344,"name":"Oncology"},{"id":57382345,"name":"Artificial Intelligence and Machine Learning"}],"tags":[],"updatedAt":"2025-10-21T23:46:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-13 19:31:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-7893373","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7893373","identity":"rs-7893373","version":["v2"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}