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

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 2015–2025. A total of 370 open-access English-language papers met 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 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 continue to exist.