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

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.