Artificial Intelligence–Related Dental Research: Bibliometric and Altmetric Analysis
Background: Recent years have witnessed an explosive surge in dental research related to artificial intelligence (AI). These applications have optimised dental workflows, demonstrating significant clinical importance. Understanding the current landscape and trends of this topic is crucial for both c...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | International Dental Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0020653924014151 |
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| author | Wei Lu Xueqian Yu Yueyang Li Yi Cao Yanning Chen Fang Hua |
| author_facet | Wei Lu Xueqian Yu Yueyang Li Yi Cao Yanning Chen Fang Hua |
| author_sort | Wei Lu |
| collection | DOAJ |
| description | Background: Recent years have witnessed an explosive surge in dental research related to artificial intelligence (AI). These applications have optimised dental workflows, demonstrating significant clinical importance. Understanding the current landscape and trends of this topic is crucial for both clinicians and researchers to utilise and advance this technology. However, a comprehensive scientometric study regarding this field had yet to be performed. Methods: A literature search was conducted in the Web of Science Core Collection database to identify eligible “research articles” and “reviews.” Literature screening and exclusion were performed by 2 investigators. Thereafter, VOSviewer was utilised 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 were described narratively and supplemented with Spearman correlation analysis. Results: A total of 1558 research publications were included. During the past 5 years, AI-related dental publications drastically increased in number, from 36 to 581. Diagnostics and Scientific Reports published the most articles, whereas Journal of Dental Research received the highest number of citations per article. China, the US, and South Korea emerged as the most prolific countries, whilst Germany received the highest number of citations per article (23.29). Charité Universitätsmedizin Berlin was the institution with the highest number of publications and citations per article (29.16). Altmetric Attention Score was correlated with News Mentions (P < .001), and significant associations were observed amongst Dimension Citations, Mendeley Readers, and Web of Science Citations (P < .001). Conclusions: The publication numbers regarding AI-related dental research have been rising rapidly and may continue their upwards trend. China, the US, South Korea, and Germany had promoted the progress of AI-related dental research. Disease diagnosis, orthodontic applications, and morphology segmentation were current hotspots. Attention mechanism, explainable AI, multimodal data fusion, and AI-generated text assistants necessitate future research and exploration. |
| format | Article |
| id | doaj-art-c92ca96565804bc69f5bbfdfa108a1d4 |
| institution | Kabale University |
| issn | 0020-6539 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Dental Journal |
| spelling | doaj-art-c92ca96565804bc69f5bbfdfa108a1d42025-01-21T04:12:44ZengElsevierInternational Dental Journal0020-65392025-02-01751166175Artificial Intelligence–Related Dental Research: Bibliometric and Altmetric AnalysisWei Lu0Xueqian Yu1Yueyang Li2Yi Cao3Yanning Chen4Fang Hua5State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, ChinaState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Library, School & Hospital of Stomatology, Wuhan University, Wuhan, ChinaWuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, Wuhan, ChinaSchool of Electronic Information, Wuhan University, Wuhan, ChinaRestorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China; Corresponding authors. Yanning Chen, Restorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong, 34 Hospital Road, Hong Kong SAR 000000, China.State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Center for Evidence-Based Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Center for Orthodontics and Pediatric Dentistry at Optics Valley Branch, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Division of Dentistry, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK; Fang Hua, Center for Evidence-Based Stomatology, School & Hospital of Stomatology, Wuhan University, 237 Luoyu Road, Wuhan 430079, China.Background: Recent years have witnessed an explosive surge in dental research related to artificial intelligence (AI). These applications have optimised dental workflows, demonstrating significant clinical importance. Understanding the current landscape and trends of this topic is crucial for both clinicians and researchers to utilise and advance this technology. However, a comprehensive scientometric study regarding this field had yet to be performed. Methods: A literature search was conducted in the Web of Science Core Collection database to identify eligible “research articles” and “reviews.” Literature screening and exclusion were performed by 2 investigators. Thereafter, VOSviewer was utilised 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 were described narratively and supplemented with Spearman correlation analysis. Results: A total of 1558 research publications were included. During the past 5 years, AI-related dental publications drastically increased in number, from 36 to 581. Diagnostics and Scientific Reports published the most articles, whereas Journal of Dental Research received the highest number of citations per article. China, the US, and South Korea emerged as the most prolific countries, whilst Germany received the highest number of citations per article (23.29). Charité Universitätsmedizin Berlin was the institution with the highest number of publications and citations per article (29.16). Altmetric Attention Score was correlated with News Mentions (P < .001), and significant associations were observed amongst Dimension Citations, Mendeley Readers, and Web of Science Citations (P < .001). Conclusions: The publication numbers regarding AI-related dental research have been rising rapidly and may continue their upwards trend. China, the US, South Korea, and Germany had promoted the progress of AI-related dental research. Disease diagnosis, orthodontic applications, and morphology segmentation were current hotspots. Attention mechanism, explainable AI, multimodal data fusion, and AI-generated text assistants necessitate future research and exploration.http://www.sciencedirect.com/science/article/pii/S0020653924014151Dental researchArtificial intelligenceDeep learningMachine learningBibliometrics |
| spellingShingle | Wei Lu Xueqian Yu Yueyang Li Yi Cao Yanning Chen Fang Hua Artificial Intelligence–Related Dental Research: Bibliometric and Altmetric Analysis International Dental Journal Dental research Artificial intelligence Deep learning Machine learning Bibliometrics |
| title | Artificial Intelligence–Related Dental Research: Bibliometric and Altmetric Analysis |
| title_full | Artificial Intelligence–Related Dental Research: Bibliometric and Altmetric Analysis |
| title_fullStr | Artificial Intelligence–Related Dental Research: Bibliometric and Altmetric Analysis |
| title_full_unstemmed | Artificial Intelligence–Related Dental Research: Bibliometric and Altmetric Analysis |
| title_short | Artificial Intelligence–Related Dental Research: Bibliometric and Altmetric Analysis |
| title_sort | artificial intelligence related dental research bibliometric and altmetric analysis |
| topic | Dental research Artificial intelligence Deep learning Machine learning Bibliometrics |
| url | http://www.sciencedirect.com/science/article/pii/S0020653924014151 |
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