Artificial Intelligence Related Dental Research: Bibliometric And Altmetric Analysis

This article aims to depict the current landscape, hotspots and upcoming trends regarding AI related dental research through bibliometric and altmetric analyses. Literature searching was conducted in the Web of Science Core Collection database to identify eligible “research articles” and “reviews”. Literature screening and exclusion were performed by two investigators. Thereafter, VOSViewer was utilized in co-occurrence analysis, and CiteSpace in co-citation analysis. R package Bibliometrix was employed to automatically calculate scientific impacts, determining the core authors and journals. Altmetric data was described narratively and supplemented with Spearman correlation analysis. A total of 1,558 research publications were included. During the past 5 years, AI-related dental publications drastically increased from 36 to 581. Diagnostics and Scientific Reports published the most articles, whereas Journal of Dental Research received the highest citations per article. China, USA, and South Korea emerged as the most prolific countries, while Germany received the highest citations per article (23.29). Charité Universitätsmedizin Berlin was the institution with the highest publications and citations per article (29.16). Altmetric Attention Score was correlated with News Mentions (p < 0.001), and significant associations were observed among Dimension Citations, Mendeley Readers and Web of Science Citations (p < 0.001). The publication numbers regarding AI-related dental research have been rising rapidly and may continue its upward trend. Disease diagnosis, orthodontic applications, and morphology segmentation were current hotspots. Attention mechanism, explainable AI, multi-modal data fusion, and AIGT assistants necessitate future research and exploration.

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Publication Details

Journal
International Dental Journal
Published
2025-10-01
DOI
https://doi.org/10.1016/j.identj.2025.104161
Primary Topic
Dental Radiography and Imaging
Type
article
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article

Artificial Intelligence Related Dental Research: Bibliometric And Altmetric Analysis

Xueqian Yu, Fang Hua, Yanning Chen, Wei Lu
International Dental Journal
Dental Radiography and Imaging
article

Artificial Intelligence Related Dental Research: Bibliometric And Altmetric Analysis

Xueqian Yu, Fang Hua, Yanning Chen, Wei Lu
article en

Abstract

This article aims to depict the current landscape, hotspots and upcoming trends regarding AI related dental research through bibliometric and altmetric analyses. Literature searching was conducted in the Web of Science Core Collection database to identify eligible “research articles” and “reviews”. Literature screening and exclusion were performed by two investigators. Thereafter, VOSViewer was utilized in co-occurrence analysis, and CiteSpace in co-citation analysis. R package Bibliometrix was employed to automatically calculate scientific impacts, determining the core authors and journals. Altmetric data was described narratively and supplemented with Spearman correlation analysis. A total of 1,558 research publications were included. During the past 5 years, AI-related dental publications drastically increased from 36 to 581. Diagnostics and Scientific Reports published the most articles, whereas Journal of Dental Research received the highest citations per article. China, USA, and South Korea emerged as the most prolific countries, while Germany received the highest citations per article (23.29). Charité Universitätsmedizin Berlin was the institution with the highest publications and citations per article (29.16). Altmetric Attention Score was correlated with News Mentions (p < 0.001), and significant associations were observed among Dimension Citations, Mendeley Readers and Web of Science Citations (p < 0.001). The publication numbers regarding AI-related dental research have been rising rapidly and may continue its upward trend. Disease diagnosis, orthodontic applications, and morphology segmentation were current hotspots. Attention mechanism, explainable AI, multi-modal data fusion, and AIGT assistants necessitate future research and exploration.

International Dental JournalVol. 75
Wuhan University (CN), University of Hong Kong (HK)
Openalex Percentile: Top 54%
Dental Radiography and Imaging
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