Abstract

CARRILLO FERNANDEZ, Armando Moisés; SIERRALTA SOTO, Mirella Pilar; DIAZ CORREA, Christian Armando  and  NUNEZ APUMAYTA, Cintia Adriana. Language Models and generative Artificial Intelligence for teaching resolutions in traumatic dental emergency situations. e-Rev. Multidiscip. Saber [online]. 2025, vol.3, e-RMS14022025.  Epub June 25, 2025. ISSN 2960-2467.  https://doi.org/10.61286/e-rms.v3i.173.

The Language Models and generative Artificial Intelligence for teaching resolutions in traumatic dental emergencies explores the use of generative Artificial Intelligence (AI) in dental training, specifically in managament of traumatic dental emergencies. Three generative AI systems (Copilot IAG-1, NEXTAI IAG-2 and Perplexity AIG-3) were evaluated using prompts designed to simulate dental emergencies situations. The results showed that these systems can provide accurate diagnoses and effective treatments recommendations, with scores above 90% in most of evaluated categories. The study highlights the consistency in diagnostic accuracy and quality of treatment recommendations, especially in the managament of acute dental pain, where all systems achieved 100% in severaldimensions. However, áreas for improvement were identified, particularly for IAG-2 in categories such as dental dislocation and gingial bleeding. Additionally, the ease of use and response time were evaluated, finding that all systems provided quick and adequate responses, with IAG-3 standing out for its speed and ease of use. The dimension of interest and motivation was also positive, suggesting that these systems can maintain a high level of engagement among users.

Keywords : dentistry; generative artificial intelligence; emergencies; traumas; evaluation; language models; education..

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