OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 08.04.2026, 17:07

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

Artificial Intelligence in Maxillofacial Radiology: A Bibliometric Study

2023·4 Zitationen·Mathews Journal of DentistryOpen Access
Volltext beim Verlag öffnen

4

Zitationen

4

Autoren

2023

Jahr

Abstract

Purpose:The aim of this study is to evaluate the global trend in Artificial Intelligence (AI) research involving maxillofacial radiology and query a large database for a comprehensive analysis for those wishing to do more research in this area.Materials & Methods: All publication searches were performed using the PubMed databases.From January 1989 to March 2022, all AI-related publications were selected using following search terms: "artificial intelligence dental radiology", "deep learning dental radiology", "machine learning dental radiology", "Convolutional Neural Network dental radiology", "neural network dental radiology".Totally, 971 articles were found, 732 articles were excluded, 239 articles were included and analyzed for the specified bibliometric criterias.Then including publications were categorized by country of origin, institution, type of article, journal name, impact factor of journal, subspecialties, study design, publication year, number of citation, AI tecnic and imaging modality.Statistical analysis was performed using IBM SPSS Statistics version 28.0(IBM, Chicago, IL).Results: According to results, an increase was observed in the number of publications over the years, the most publications were made in 2021(100) and the most publications from Korea (48).The institution that conducts the most studies on AI is Charité-Universitätsmedizin (8.44%) and the journal in which the studies are published the most is Dentomaxillofacial radiology (24%).The most cited publication was the Korean study published in 2018, with 283 citations.Panoramic radiograph (75) was the most used imaging technique, and CNN (99) was used from AI techniques.Conclusion: This analysis provides researchers with a comprehensive overview of AIrelated research in maxillofacial radiology, providing guidance for future studies.

Ähnliche Arbeiten

Autoren

Institutionen

Themen

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical ImagingAdvanced X-ray and CT Imaging
Volltext beim Verlag öffnen