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Artificial Intelligence-Related Dental Research: Bibliometric and Altmetric Analysis.

作者信息

Lu Wei, Yu Xueqian, Li Yueyang, Cao Yi, Chen Yanning, Hua Fang

机构信息

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.

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; Library, School & Hospital of Stomatology, Wuhan University, Wuhan, China.

出版信息

Int Dent J. 2025 Feb;75(1):166-175. doi: 10.1016/j.identj.2024.08.004. Epub 2024 Sep 11.


DOI:10.1016/j.identj.2024.08.004
PMID:39266401
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11806303/
Abstract

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.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/580a5cd704d9/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/102eacbf729d/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/c94059c088de/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/bb30ed8b4869/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/aad6e5826a4f/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/580a5cd704d9/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/102eacbf729d/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/c94059c088de/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/bb30ed8b4869/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/aad6e5826a4f/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/11806303/580a5cd704d9/gr5.jpg

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本文引用的文献

[1]
Familiarity with ChatGPT Features Modifies Expectations and Learning Outcomes of Dental Students.

Int Dent J. 2024-12

[2]
Determination of the pubertal growth spurt by artificial intelligence analysis of cervical vertebrae maturation in lateral cephalometric radiographs.

Oral Surg Oral Med Oral Pathol Oral Radiol. 2024-8

[3]
The online attention analysis on orthognathic surgery research.

J Stomatol Oral Maxillofac Surg. 2024-6

[4]
Towards clinically applicable automated mandibular canal segmentation on CBCT.

J Dent. 2024-5

[5]
Top 100 most cited papers on diagnostic aids for oral cancer: A bibliometric analysis.

J Stomatol Oral Maxillofac Surg. 2024-12

[6]
Performance of Generative Artificial Intelligence in Dental Licensing Examinations.

Int Dent J. 2024-6

[7]
Generative adversarial networks in dental imaging: a systematic review.

Oral Radiol. 2024-4

[8]
Automatic caries detection in bitewing radiographs: part I-deep learning.

Clin Oral Investig. 2023-12

[9]
Time efficiency, occlusal morphology, and internal fit of anatomic contour crowns designed by dental software powered by generative adversarial network: A comparative study.

J Dent. 2023-11

[10]
Artificial intelligence in orthodontics and orthognathic surgery: a bibliometric analysis of the 100 most-cited articles.

Head Face Med. 2023-8-23

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