Current research status and frontiers of Artificial Intelligence in Stomatology: A Bibliometric Analysis (2010-2022)

Abstract

Abstract Objective: In medicine, artificial intelligence (AI)-based research is growing rapidly and has become a research hotspot in Stomatology. Using bibliometric analyses, we reviewed the literature on AI in Stomatology (AIIS) between 2010 and 2022 to identify frontiers and research hotspots in this field. Methods: On the 7 th January 2023, we retrieved 1121 studies, published between 2010 and 2022, from the Web of Science Core Collection. We conducted bibliometric analyses using CiteSpace, VOSview, R package bibliometrix, and Microsoft Office Excel. Results: We identified 1008 AIIS articles and 113 reviews published between 2010 and 2022. Publications increased rapidly from 2018; China had the most publications, but the USA had the highest H-index. Yonsei and Seoul National Universities were the most productive institutes, and Scientific Reports was the main AIIS publication journal. Reference clusters were classified into six headings: panoramic radiograph, cephalometric landmark detection, deep convolutional neural network (DCNN)-based automated segmentation, caries detection, oral cancer (OC), and automatic classification. Research hotspots and frontiers were represented by dental caries (2020–2022), dental implants (2020–2022), oral squamous cell carcinoma (OSCC) (2020–2022), and computed tomography (CT) (2019–2021). Conclusions: We objectively summarized the AIIS literature in this bibliometric analysis. According to our analysis, the number of publications related to AIIS began to increase significantly from 2018, and additionally, the current frontiers and research hotspots were identified. Clinical relevance: This bibliometric analysis provided an overview of Artificial Intelligence in Stomatology. Study knowledge and information, especially hotspots and frontiers, will help scientists studying AIIS lay the foundations for future research.

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