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Article: Unlocking the Potentials of Large Language Models in Orthodontics: A Scoping Review

TitleUnlocking the Potentials of Large Language Models in Orthodontics: A Scoping Review
Authors
Issue Date13-Nov-2024
PublisherMDPI
Citation
Bioengineering, 2024, v. 11, n. 11 How to Cite?
Abstract

(1) Background: In recent years, large language models (LLMs) such as ChatGPT have gained significant attention in various fields, including dentistry. This scoping review aims to examine the current applications and explore potential uses of LLMs in the orthodontic domain, shedding light on how they might improve dental healthcare. (2) Methods: We carried out a comprehensive search in five electronic databases, namely PubMed, Scopus, Embase, ProQuest and Web of Science. Two authors independently screened articles and performed data extraction according to the eligibility criteria, following the PRISMA-ScR guideline. The main findings from the included articles were synthesized and analyzed in a narrative way. (3) Results: A total of 706 articles were searched, and 12 papers were eventually included. The applications of LLMs include improving diagnostic and treatment efficiency in orthodontics as well as enhancing communication with patients. (4) Conclusions: There is emerging research in countries worldwide on the use of LLMs in orthodontics, suggesting an upward trend in their acceptance within this field. However, the potential application of LLMs remains in its early stage, with a noticeable lack of extensive studies and tailored products to address specific clinical needs.


Persistent Identifierhttp://hdl.handle.net/10722/351307
ISSN
2023 Impact Factor: 3.8
2023 SCImago Journal Rankings: 0.627

 

DC FieldValueLanguage
dc.contributor.authorZheng, Jie-
dc.contributor.authorDing, Xiaoqian-
dc.contributor.authorPu, Jingya Jane-
dc.contributor.authorChung, Sze Man-
dc.contributor.authorAi, Qi Yong H-
dc.contributor.authorHung, Kuo Feng-
dc.contributor.authorShan, Zhiyi-
dc.date.accessioned2024-11-19T00:35:27Z-
dc.date.available2024-11-19T00:35:27Z-
dc.date.issued2024-11-13-
dc.identifier.citationBioengineering, 2024, v. 11, n. 11-
dc.identifier.issn2306-5354-
dc.identifier.urihttp://hdl.handle.net/10722/351307-
dc.description.abstract<p>(1) Background: In recent years, large language models (LLMs) such as ChatGPT have gained significant attention in various fields, including dentistry. This scoping review aims to examine the current applications and explore potential uses of LLMs in the orthodontic domain, shedding light on how they might improve dental healthcare. (2) Methods: We carried out a comprehensive search in five electronic databases, namely PubMed, Scopus, Embase, ProQuest and Web of Science. Two authors independently screened articles and performed data extraction according to the eligibility criteria, following the PRISMA-ScR guideline. The main findings from the included articles were synthesized and analyzed in a narrative way. (3) Results: A total of 706 articles were searched, and 12 papers were eventually included. The applications of LLMs include improving diagnostic and treatment efficiency in orthodontics as well as enhancing communication with patients. (4) Conclusions: There is emerging research in countries worldwide on the use of LLMs in orthodontics, suggesting an upward trend in their acceptance within this field. However, the potential application of LLMs remains in its early stage, with a noticeable lack of extensive studies and tailored products to address specific clinical needs.<br></p>-
dc.languageeng-
dc.publisherMDPI-
dc.relation.ispartofBioengineering-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleUnlocking the Potentials of Large Language Models in Orthodontics: A Scoping Review-
dc.typeArticle-
dc.identifier.doi10.3390/bioengineering11111145-
dc.identifier.volume11-
dc.identifier.issue11-
dc.identifier.eissn2306-5354-
dc.identifier.issnl2306-5354-

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