Comparing the performance of ChatGPT, Gemini, and Claude in English and Polish on medical examinations

Abstract

In the realm of medical education, the utility of chatbots is being explored with growing interest. One pertinent area of investigation is the performance of these models on standardized medical examinations, which are crucial for certifying the knowledge and readiness of healthcare professionals. In Poland, dental and medical students have to pass crucial exams known as LDEK (Medical-Dental Final Examination) and LEK (Medical Final Examination) exams respectively. The primary objective of this study was to conduct a comparative analysis of chatbots: ChatGPT-4, Gemini and Claude to evaluate their accuracy in answering exam questions of the LDEK and the Medical-Dental Verification Examination (LDEW), using queries in both English and Polish. The analysis of Generalized Linear Mixed-Effects Model, which compared chatbots within question groups, showed that the chatbot Claude achieved the highest probability of accuracy for all question groups except the area of prosthetic dentistry compared to ChatGPT-4 and Gemini. In addition, the probability of a correct answer to questions in the field of integrated medicine was higher than in the field of dentistry for all chatbots in both prompt languages. Our results demonstrated that Claude achieved the highest accuracy in all areas analysed and outperformed other chatbots. This suggests that Claude has significant potential to support the medical education of dental students. This study showed that the performance of chatbots varied depending on the prompt language and the specific field. This highlights the importance of considering language and specialty when selecting a chatbot for educational purposes.

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