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Background <p>The objective of this study was to evaluate the performance of ScholarGPT, ChatGPT-4o and Google Gemini in responding to queries pertaining to endodontic apical surgery, a subject that demands advanced specialist knowledge in endodontics.</p> Methods <p>A total of 30 questions, including 12 binary and 18 open-ended queries, were formulated based on information on endodontic apical surgery taken from a well-known endodontic book called Cohen’s pathways of the pulp (12th edition). The questions were posed by two different researchers using different accounts on the ScholarGPT, ChatGPT-4o and Gemini platforms. The responses were then coded by the researchers and categorised as ‘correct’, ‘incorrect’, or ‘insufficient’. The Pearson chi-square test was used to assess the relationships between the platforms.</p> Results <p>A total of 5,400 responses were evaluated. Chi-square analysis revealed statistically significant differences between the accuracy of the responses provided applications (χ² = 22.61; <i>p</i> &lt; 0.05). ScholarGPT demonstrated the highest rate of correct responses (97.7%), followed by ChatGPT-4o with 90.1%. Conversely, Gemini exhibited the lowest correct response rate (59.5%) among the applications examined.</p> Conclusions <p>ScholarGPT performed better overall on questions about endodontic apical surgery than ChatGPT-4o and Gemini. GPT models based on academic databases, such as ScholarGPT, may provide more accurate information about dentistry. However, additional research should be conducted to develop a GPT model that is specifically tailored to the field of endodontics.</p>

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Assessment of various artificial intelligence applications in responding to technical questions in endodontic surgery

  • 期刊论文

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  • 发表日期：

    2025年5月22日

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  • Sevda Durust Baris,
  • Kubilay Baris

摘要

Background

The objective of this study was to evaluate the performance of ScholarGPT, ChatGPT-4o and Google Gemini in responding to queries pertaining to endodontic apical surgery, a subject that demands advanced specialist knowledge in endodontics.

Methods

A total of 30 questions, including 12 binary and 18 open-ended queries, were formulated based on information on endodontic apical surgery taken from a well-known endodontic book called Cohen’s pathways of the pulp (12th edition). The questions were posed by two different researchers using different accounts on the ScholarGPT, ChatGPT-4o and Gemini platforms. The responses were then coded by the researchers and categorised as ‘correct’, ‘incorrect’, or ‘insufficient’. The Pearson chi-square test was used to assess the relationships between the platforms.

Results

A total of 5,400 responses were evaluated. Chi-square analysis revealed statistically significant differences between the accuracy of the responses provided applications (χ² = 22.61; p < 0.05). ScholarGPT demonstrated the highest rate of correct responses (97.7%), followed by ChatGPT-4o with 90.1%. Conversely, Gemini exhibited the lowest correct response rate (59.5%) among the applications examined.

Conclusions

ScholarGPT performed better overall on questions about endodontic apical surgery than ChatGPT-4o and Gemini. GPT models based on academic databases, such as ScholarGPT, may provide more accurate information about dentistry. However, additional research should be conducted to develop a GPT model that is specifically tailored to the field of endodontics.