Introduction: Artificial intelligence (AI) can be described as the combination of computer sciences and linguistics, objective building machines capable of performing various tasks that otherwise would need Human Intelligence. One of the many AI based tools that has gained popularity is the Chat–Generative Pre–Trained Transformer (ChatGPT). Due to the popularity and its massive media coverage, incorrect and misleading information provided by ChatGPT will have a profound impact on patient misinformation. Furthermore, it may cause mistreatment and misdiagnosis as ChatGPT can mislead physicians on the decision–making pathway. Objective: Eevaluate and assess the accuracy and reproducibility of ChatGPT answers regarding common pediatric urological diagnoses. Methods: ChatGPT 3.5 version was used. The questions asked for the program involved Primary Megaureter (pMU), Enuresis and Vesicoureteral Reflux (VUR). There were three queries for each topic, adding up to 9 in total. The queries were inserted into ChatGPT twice, and both responses were recorded to examine the reproducibility of ChatGPT′s answers. After that analysis, both questions were combined, forming a single answer. Afterwards, those responses were evaluated qualitatively by a board of three specialists with a deep expertise in the field. A descriptive analysis was performed. Results: ChatGPT demonstrated general knowledge on the researched topics, including the definition, diagnosis, and treatment of Enuresis, VUR and pMU. Regarding Enuresis, the provided definition was partially correct, as the generic response allowed for misinterpretation. As for the definition of VUR, the response was considered appropriate. And for pMU it was partially correct, lacking essential aspects of its definition such as the diameter of the dilatation of the ureter. Unnecessary exams were suggested, for both Enuresis and pMU. Regarding the treatment of the conditions mentioned, it specified treatments to Enuresis that are known to be ineffective, such as bladder training. Discussion: AI has a wide potential to bring several benefits to medical knowledge, improving decision–making and patient education. However, following the reports on the literature, we found a lack of genuine clinical experience and judgment from ChatGPT, performing well in less complex questions, yet with a steep decrease on its performance as the complexity of the queries increase. Therefore, providing wrong answers to crucial topics. Conclusion: ChatGPT responses present a combination of accurate and relevant information, but also incomplete, ambiguous and, occasionally, misleading details, especially regarding the treatment of the investigated diseases. Because of that, it is not recommended to make clinical decisions based exclusively on ChatGPT.

The authors have declared no competing interest.

No funding was received for this study from any public or commercial source.

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