Artificial Intelligence Applications in Oral and Maxillofacial Radiology: A Bibliometric Analysis

Abstract

Artificial intelligence (AI) has increasingly shaped research and clinical practice in oral and maxillofacial radiology, particularly with the widespread use of digital imaging modalities. The rapid growth of AI-related publications has resulted in an expanding body of literature, making it difficult to comprehensively evaluate research trends and thematic developments in the field.This study aimed to conduct a bibliometric analysis of scientific publications focusing on artificial intelligence applications in oral and maxillofacial radiology. A literature search was performed using the Web of Science Core Collection database, covering publications from 1994 to 2025. Bibliometric analyses were carried out using the bibliometrix package and Biblioshiny to assess publication trends, citation patterns, leading journals, authors, countries, institutions, and keyword-based conceptual structures. Artificial intelligence–supported analytical methods were applied to examine thematic structures within the literature.The results showed a marked increase in AI-related research output after 2018, with China, the United States, and South Korea emerging as the most productive countries. Keyword co-occurrence analysis identified dominant thematic clusters related to artificial intelligence, deep learning, machine learning, and classification, highlighting the prominence of data-driven approaches in image analysis and diagnosis.Overall, this bibliometric analysis provides a structured overview of the evolution and current landscape of artificial intelligence research in oral and maxillofacial radiology, emphasizing the growing integration of AI-driven methodologies within the field.

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