Bibliometric analysis of deep learning applications in dentistry
Yazarlar (4)
Dr. Öğr. Üyesi Elham Tahsın Yasın YASIN Selçuk Üniversitesi, Türkiye
Mediha Erturk
Melek Tassoker Bulut
Murat Koklu
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | International Dental Journal (Q1) | ||
| Dergi ISSN | 0020-6539 Dergi Bilgileri (2024) | ||
| Dergi Tarandığı Indeksler | |||
| Makale Dili | İngilizce | Basım Tarihi | 10-2024 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 18-10-2024 |
| Cilt / Sayı / Sayfa | 74 / 0 / 216–216 | DOI | 10.1016/j.identj.2024.07.044 |
| Makale Linki | https://linkinghub.elsevier.com/retrieve/pii/S0020653924002363 | ||
| UAK Araştırma Alanları |
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| Özet |
| AIM or PURPOSEDeep learning techniques have significantly impacted various aspects of dentistry, including diagnosis, treatment planning, and patient care. This paper aims to explore the influence and patterns of deep learning methodologies in dentistry using bibliometric analysis.MATERIALS and METHODA comprehensive search of the Web of Science database was conducted, yielding 1,228 relevant articles published between 2014 and 2024. Bibliometric analyses, including keyword co-occurrence, author co-authorship, country co-authorship, author citation, document bibliographic coupling, organization bibliographic coupling, and reference co-citation, were performed using VOSviewer software.RESULTSAmong the total publications, a remarkable 94.95% were published after 2018. The United States and Japan emerged as the leading nations, contributing 20.6% and 18.48% of the articles, respectively ... |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 3 |