Implications of large language models such as ChatGPT for dental medicine.

artificial intelligence dental care dental education evidence-based dentistry machine learning

Journal

Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
ISSN: 1708-8240
Titre abrégé: J Esthet Restor Dent
Pays: England
ID NLM: 101096515

Informations de publication

Date de publication:
10 2023
Historique:
revised: 25 03 2023
received: 07 03 2023
accepted: 28 03 2023
medline: 23 10 2023
pubmed: 6 4 2023
entrez: 5 4 2023
Statut: ppublish

Résumé

This article provides an overview of the implications of ChatGPT and other large language models (LLMs) for dental medicine. ChatGPT, a LLM trained on massive amounts of textual data, is adept at fulfilling various language-related tasks. Despite its impressive capabilities, ChatGPT has serious limitations, such as occasionally giving incorrect answers, producing nonsensical content, and presenting misinformation as fact. Dental practitioners, assistants, and hygienists are not likely to be significantly impacted by LLMs. However, LLMs could affect the work of administrative personnel and the provision of dental telemedicine. LLMs offer potential for clinical decision support, text summarization, efficient writing, and multilingual communication. As more people seek health information from LLMs, it is crucial to safeguard against inaccurate, outdated, and biased responses to health-related queries. LLMs pose challenges for patient data confidentiality and cybersecurity that must be tackled. In dental education, LLMs present fewer challenges than in other academic fields. LLMs can enhance academic writing fluency, but acceptable usage boundaries in science need to be established. While LLMs such as ChatGPT may have various useful applications in dental medicine, they come with risks of malicious use and serious limitations, including the potential for misinformation. Along with the potential benefits of using LLMs as an additional tool in dental medicine, it is crucial to carefully consider the limitations and potential risks inherent in such artificial intelligence technologies.

Identifiants

pubmed: 37017291
doi: 10.1111/jerd.13046
doi:

Substances chimiques

Fenbendazole 621BVT9M36

Types de publication

Journal Article Review Research Support, Non-U.S. Gov't

Langues

eng

Pagination

1098-1102

Subventions

Organisme : Freiwillige Akademische Gesellschaft
Organisme : Gottfried und Julia Bangerter-Rhyner-Stiftung

Informations de copyright

© 2023 The Authors. Journal of Esthetic and Restorative Dentistry published by Wiley Periodicals LLC.

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Auteurs

Florin Eggmann (F)

Department of Preventive and Restorative Sciences, Penn Dental Medicine, Robert Schattner Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Department of Periodontology, Endodontology, and Cariology, University Center for Dental Medicine Basel UZB, University of Basel, Basel, Switzerland.

Roland Weiger (R)

Department of Periodontology, Endodontology, and Cariology, University Center for Dental Medicine Basel UZB, University of Basel, Basel, Switzerland.

Nicola U Zitzmann (NU)

Department of Reconstructive Dentistry, University Center for Dental Medicine Basel UZB, University of Basel, Basel, Switzerland.

Markus B Blatz (MB)

Department of Preventive and Restorative Sciences, Penn Dental Medicine, Robert Schattner Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

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