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Performance of an Artificial Intelligence–Based Chatbot (ChatGPT) Answering the European Certification in Implant Dentistry Exam

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Název: Performance of an Artificial Intelligence–Based Chatbot (ChatGPT) Answering the European Certification in Implant Dentistry Exam
Autoři: Revilla‐León, Marta, Barmak, Basir A., Sailer, Irena, Kois, John C., Att, Wael
Zdroj: The International Journal of Prosthodontics. 37:221-224
Informace o vydavateli: Quintessence Publishing, 2024.
Rok vydání: 2024
Témata: Europe, Dental Implantation, Certification, Artificial Intelligence, 617.6, Educational Measurement / methods, Humans, Educational Measurement, Dental Implantation / education, Software
Popis: To compare the performance of licensed dentists and two software versions (3.5 legacy and 4.0) of an artificial intelligence (AI)-based chatbot (ChatGPT) answering the exam for the 2022 Certification in Implant Dentistry of the European Association for Osseointegration (EAO).The 50-question, multiple-choice exam of the EAO for the 2022 Certification in Implant Dentistry was obtained. Three groups were created based on the individual or program answering the exam: licensed dentists (D group) and two software versions of an artificial intelligence (AI)-based chatbot (ChatGPT)-3.5 legacy (ChatGPT-3.5 group) and the 4.0 version (ChatGPT-4.0 group). The EAO provided the results of the 2022 examinees (D group). For the ChatGPT groups, the 50 multiple-choice questions were introduced into both ChatGBT versions, and the answers were recorded. Pearson correlation matrix was used to analyze the linear relationship among the subgroups. The inter- and intraoperator reliability was calculated using Cronbach's alpha coefficient. One-way ANOVA and Tukey post-hoc tests were used to examine the data (α = .05).ChatGPT was able to pass the exam for the 2022 Certification in Implant Dentistry of the EAO. Additionally, the software version of ChatGPT impacted the score obtained. The 4.0 version not only pass the exam but also obtained a significantly higher score than the 3.5 version and licensed dentists completing the same exam.The AIbased chatbot tested not only passed the exam but performed better than licensed dentists.
Druh dokumentu: Article
Popis souboru: application/pdf
ISSN: 0893-2174
DOI: 10.11607/ijp.8852
Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38270461
https://archive-ouverte.unige.ch/unige:183377
https://doi.org/10.11607/ijp.8852
Přístupové číslo: edsair.doi.dedup.....48c7f12c5a0631b3ed411295c22ff4a9
Databáze: OpenAIRE
Popis
Abstrakt:To compare the performance of licensed dentists and two software versions (3.5 legacy and 4.0) of an artificial intelligence (AI)-based chatbot (ChatGPT) answering the exam for the 2022 Certification in Implant Dentistry of the European Association for Osseointegration (EAO).The 50-question, multiple-choice exam of the EAO for the 2022 Certification in Implant Dentistry was obtained. Three groups were created based on the individual or program answering the exam: licensed dentists (D group) and two software versions of an artificial intelligence (AI)-based chatbot (ChatGPT)-3.5 legacy (ChatGPT-3.5 group) and the 4.0 version (ChatGPT-4.0 group). The EAO provided the results of the 2022 examinees (D group). For the ChatGPT groups, the 50 multiple-choice questions were introduced into both ChatGBT versions, and the answers were recorded. Pearson correlation matrix was used to analyze the linear relationship among the subgroups. The inter- and intraoperator reliability was calculated using Cronbach's alpha coefficient. One-way ANOVA and Tukey post-hoc tests were used to examine the data (α = .05).ChatGPT was able to pass the exam for the 2022 Certification in Implant Dentistry of the EAO. Additionally, the software version of ChatGPT impacted the score obtained. The 4.0 version not only pass the exam but also obtained a significantly higher score than the 3.5 version and licensed dentists completing the same exam.The AIbased chatbot tested not only passed the exam but performed better than licensed dentists.
ISSN:08932174
DOI:10.11607/ijp.8852