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This study analyzed the performance of LLMAs on solving restorative dentistry and endodontics (RDE) student assessment questions.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Materials and methods<\/jats:title>\n                <jats:p>151 questions from a RDE question pool were prepared for prompting using LLMAs from OpenAI (ChatGPT-3.5,-4.0 and -4.0o) and Google (Gemini 1.0). Multiple-choice questions were sorted into four question subcategories, entered into LLMAs and answers recorded for analysis. P-value and chi-square statistical analyses were performed using Python 3.9.16.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The total answer accuracy of ChatGPT-4.0o was the highest, followed by ChatGPT-4.0, Gemini 1.0 and ChatGPT-3.5 (72%, 62%, 44% and 25%, respectively) with significant differences between all LLMAs except GPT-4.0 models. The performance on subcategories direct restorations and caries was the highest, followed by indirect restorations and endodontics.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>Overall, there are large performance differences among LLMAs. Only the ChatGPT-4 models achieved a success ratio that could be used with caution to support the dental academic curriculum.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Clinical relevance<\/jats:title>\n                <jats:p>While LLMAs could support clinicians to answer dental field-related questions, this capacity depends strongly on the employed model. The most performant model ChatGPT-4.0o achieved acceptable accuracy rates in some subject sub-categories analyzed.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00784-024-05968-w","type":"journal-article","created":{"date-parts":[[2024,10,7]],"date-time":"2024-10-07T07:01:54Z","timestamp":1728284514000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":59,"title":["Performance of large language artificial intelligence models on solving restorative dentistry and endodontics student assessments"],"prefix":"10.1007","volume":"28","author":[{"given":"Paul","family":"K\u00fcnzle","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"Paris","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,10,7]]},"reference":[{"key":"5968_CR1","unstructured":"OpenAI (2022) Introducing ChatGPT. https:\/\/openai.com\/blog\/chatgpt. 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