Accuracy, consistency, and contextual understanding of large language models in restorative dentistry and endodontics
The findings underscore the potential of advanced LLMs and context-based prompting in restorative dentistry and endodontics.
Authors
- Benoit Ballester (ORCID: https://orcid.org/0000-0002-2181-5925)
- Raphaël Richert (ORCID: https://orcid.org/0000-0002-9298-1293)
- Olivia Kérourédan (ORCID: https://orcid.org/0000-0001-7967-5569)
- Claire Lafourcade
Institutions
- Université Claude Bernard Lyon 1 (FR)
- Centre National de la Recherche Scientifique (FR)
- Université de Bordeaux (FR)
- Inserm (FR)
- Université de Lyon (FR)
- Centre Hospitalier Universitaire de Bordeaux (FR)
- Bordeaux Population Health (FR)
- Economic & Social Sciences, Health Systems & Medical Informatics (FR)
- Institut de Recherche pour le Développement (FR)
- Institut National des Sciences Appliquées de Lyon (FR)
Publication Details
- Journal
- Journal of Dentistry
- Published
- 2025-04-15
- DOI
- https://doi.org/10.1016/j.jdent.2025.105764
- Citations
- 4
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 2.62