Objective: Artificial intelligence (AI) based large language models (LLMs) have recently become an effective and efficient tool in education and learning. The purpose of this study is to comparatively evaluate the accuracy of the answers given by different AI-supported chatbots to the Medical Pat hology questions asked in the Dentistry Specialization Education Entrance Exams (DSE). Material and Methods: A total of 52 pathology questions from 13 exams published on the official website of Student Selection and Placement Center (Öğrenci Seçme ve Yerleştirme Merkezi) were included in the study. Questions were directed simultaneously to LLMs by a single operator. Chi-square analysis was used to compare correct response rates among LLMs in all questions. Results: The order of correct answer rates of LLMs to all questions was as follows: ChatGPT-4o (100%), Chat GPT4 (96.15%), Gemini 2.0 (90.38%) and Claude 3 Sonnet (90.38%), Gemini 1.5 (86.53%), Co-pilot (76.92%). In general, correct answer percentages of LLMs in basic pathology questions were higher than in clinical pathology questions. While no statistically significant difference was observed between correct answers of LLMs to basic pathology questions (p=0.542), a significant difference was observed between correct answers of LLMs in clinical pathology and all questions (p<0.05). Conclusion: In this study, the highest accuracy rate was found in GPT-4o and the lowest rate was found in Co-Pilot. The findings show that LLMs have the potential to be used as a supportive tool for students and academics in pathology education.
Ekici et al. (2026) studied this question.