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Exploring the landscape of artificial intelligence in dental and maxillofacial radiology: a bibliometric analysis of studies and trends

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5Institutions déclarées
3Pays d’affiliation déclarés

Résumé fourni par la source

Background: The integration of artificial intelligence (AI) in dental and maxillofacial radiology is revolutionizing diagnostic accuracy and clinical decision-making. This bibliometric analysis investigates the research landscape, emerging trends, and scholarly impact of AI applications in this specialized field. Methods: A comprehensive search was conducted on 25 December 2024 using the Web of Science Core Collection database. Data analysis tools, including VOSviewer, CiteSpace, and Biblioshiny, were employed to examine publication trends, global contributions, collaborative networks, and keyword dynamics. Results: The analysis revealed a marked increase in AI-related publications in dental and maxillofacial radiology, particularly from 2016 onward. The number of studies rose steadily, reaching 218 publications in 2024. The United States led in research output, followed closely by China and South Korea, with KU Leuven emerging as the top-contributing institution. Reinhilde Jacobs was identified as the most prolific author, while Medical Physics was the most cited journal. Co-citation analysis highlighted influential works by authors such as J.H. Lee and F. Schwendicke . Keywords including "artificial intelligence," "deep learning," "CBCT," and "classification" dominated research discussions, reflecting the field's evolving focus. Recent research trends emphasize advanced applications in segmentation, accuracy enhancement, and predictive modeling. Conclusion: AI has become integral to the advancement of dental and maxillofacial radiology, offering significant improvements in diagnostic precision and treatment planning. This study underscores the importance of staying abreast of AI innovations to enhance patient care and foster future research opportunities. Researchers and clinicians are encouraged to adopt AI-driven approaches to maximize clinical efficiency and outcomes.

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Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Exploring the landscape of artificial intelligence in dental and maxillofacial radiology: a bibliometric analysis of studies and trends
Date Crossref
02/06/2026
Éditeur
Ovid Technologies (Wolters Kluwer Health)
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.

Institutions déclarées

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Sujets associés

Artificial Intelligence in Healthcare and EducationDental Radiography and ImagingRadiomics and Machine Learning in Medical Imaging

BNTIC News n’est pas le producteur de ces données. Recherche à la demande dans Crossref et Europe PMC, sans clé ; OpenAlex reste optionnel. Aucun service payant requis, aucune réponse conservée. Sources et limites.