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Introduction: In the 21st century's era of rapid technological advancement, ChatGPT-3.5, an artificial intelligence (AI) language model, is scrutinized for its application in dermatology. Using 119 questions from the National Specialist Examination (PES), we assess ChatGPT-3.5's performance by comparing it to human skills and addressing ethical implications. Our primary aim is to evaluate ChatGPT-3.5's proficiency in responding to 119 dermatology questions from the PES. The study emphasizes ethical considerations and compares the model's knowledge and skills to those of human dermatologists. Material and methods: Utilizing the 2023 PES question database, questions were categorized by Bloom's taxonomy and thematic content. ChatGPT-3.5, version of 3 August 2023, answered 119 questions in five sessions, allowing for a probabilistic evaluation. Statistical analyses, conducted using R Studio, assessed correctness, confidence, and difficulty. Results: ChatGPT-3.5 achieved a 49.58% correct response rate, below the 60% passing threshold. No significant differences in difficulty or correlations between difficulty and certainty were observed. Varied performance across question types highlighted strengths and weaknesses. Despite suboptimal results, ChatGPT-3.5's differential performance offers insights, suggesting future improvements. The study advocates for ongoing research into AI integration in dermatology, envisioning a promising role for AI in assisting dermatologists. Conclusions: Ethical considerations are crucial for effective AI introduction, minimizing errors, and enhancing dermatological healthcare quality, fostering optimism for AI's evolving role in dermatology. [ABSTRACT FROM AUTHOR]

Introduction: The development of Artificial Intelligence (AI) and attempts to use it in medicine are increasingly becoming the subject of more scientific research. Aim: The aim of this article is to present the effectiveness of the advanced language model, ChatGPT-3.5 in the context of the pass rate of the Polish National Specialist Examination (PES) in allergology. Additionally, it seeks to comprehend the potential applications of artificial intelligence in the field of medicine, particularly within allergology. Material and methods: The study used the latest available PES exam prepared by the Medical Research Centre in Lodz. 118 questions were asked using the openai.com platform, which allows free access to the ChatGPT-3.5 model. All questions were classified according to Bloom's taxonomy to assess their complexity and difficulty, with additional three categorisations. Each question was asked five times. Results: ChatGPT-3.5 did not pass the allergology PES, achieving a score of 52.54%. It was observed that the model performed better in answering memory questions (60%) compared to those requiring comprehension and critical thinking, where the results were slightly lower (45%). Moreover, within the categories of 'treatment', 'immune system' and 'symptoms', the model exceeded the passing threshold. Questions to which ChatGPT provided the correct answer significantly exhibited higher difficulty compared to those to which it provided an incorrect response. Conclusions: The results indicate that ChatGPT's pass rate in the allergology PES is considerably lower than that of resident doctors specializing in this field. The potential applications of AI in medicine require further research to effectively support clinical practice among physicians. [ABSTRACT FROM AUTHOR]