Kokulu, KamilDemirtaş, Mehmet SemihSert, Ekrem T.Mutlu, Hüseyin2025-02-242025-02-2420240300-9572https://dx.doi.org/10.1016/j.resuscitation.2024.110451https://hdl.handle.net/20.500.12451/12945The development of artificial intelligence (AI) tools, such as large language models (LLMs), holds significant promise for enhancing patient care and medical education. ChatGPT (Chat Generative Pre-trained Transformer), an LLM developed by OpenAI utilizing the GPT-4 architecture, currently demonstrates the highest level of medical domain knowledge among its peers.1 While ChatGPT’s performance has been assessed in various medical examinations,2,3 its capabilities in pediatric resuscitation and advanced life support remain unexplored. This study aimed to evaluate the clinical reasoning ability of ChatGPT by testing its performance on the American Heart Association (AHA) Pediatric Advanced Life Support (PALS) exam.eninfo:eu-repo/semantics/embargoedAccessChatGPTPediatric AdvanceLetter20510.1016/j.resuscitation.2024.110451Q1