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<h4>Introduction</h4>Artificial Intelligence (AI) is transforming dental education (DE) by advancing teaching strategies, clinical training, and patient care. Its integration allows for personalized learning experiences and realistic simulations, and equips students with the competencies required to deliver high-quality oral healthcare in a digital environment.<h4>Aim</h4>This project, a collaboration between the Faculty of Dentistry, Oral and Craniofacial Sciences and the Department of Informatics at King's College London, explores the impact of Large Language Models (LLMs) in preparing preclinical undergraduate oral health students for clinical practice, specifically in developing communication skills related to patient behaviour change.<h4>Methods</h4>LLMs were employed to simulate authentic dental scenarios through three iterations of Generative Language Model AI: Two text-based and one voice-based platform. In the initial phase, a comprehensive dataset of question-and-answer pairs was collaboratively created to train the system in addressing a broad spectrum of dental queries. The technology incorporates a medical information database and uses Retrieval Augmented Generation (RAG) to deliver accurate responses. LangChain and prompt engineering were also applied to ensure fair and unbiased content generation.<h4>Results</h4>These platforms were piloted with volunteer clinical staff and students at King's, whose feedback informed refinements ahead of a planned rollout to second-year dental and dental hygiene therapy students in the 2024-25 academic year. In the next phase, AI-facilitated learning experiences will be compared with traditional actor-led communication tutorials. Online questionnaires will be used to assess learning outcomes and student satisfaction across both formats, followed by focus group discussions. Initial results from the pilot were promising, indicating that AI-based platforms can effectively support the development of communication skills in preclinical oral healthcare students. Integrating AI into DE fosters early acquisition of essential professional competencies, aiming to prepare ethically responsible and skilled practitioners while contributing to the evolution of the discipline.
Abstract: PubMed · Datensatz
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- CrossRef Listing of Deleted DOIs
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- 2000-01-01
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- 0849-6757
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(2000). 10.1111/acn.v9999.9999. CrossRef Listing of Deleted DOIs. https://doi.org/10.1111/eje.70282