Sahin, Mehmet FatihTopkac, Erdem CanDogan, CagriSeramet, SerkanOzcan, RidvanAkgul, MuratYazici, Cenk Murat2024-10-292024-10-2920240892-77901557-900Xhttps://doi.org/10.1089/end.2024.0474https://hdl.handle.net/20.500.11776/14422Objective: To evaluate and compare the quality and comprehensibility of answers produced by five distinct artificial intelligence (AI) chatbots-GPT-4, Claude, Mistral, Google PaLM, and Grok-in response to the most frequently searched questions about kidney stones (KS).Materials and Methods: Google Trends facilitated the identification of pertinent terms related to KS. Each AI chatbot was provided with a unique sequence of 25 commonly searched phrases as input. The responses were assessed using DISCERN, the Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P), the Flesch-Kincaid Grade Level (FKGL), and the Flesch-Kincaid Reading Ease (FKRE) criteria.Results: The three most frequently searched terms were stone in kidney, kidney stone pain, and kidney pain. Nepal, India, and Trinidad and Tobago were the countries that performed the most searches in KS. None of the AI chatbots attained the requisite level of comprehensibility. Grok demonstrated the highest FKRE (55.6 +/- 7.1) and lowest FKGL (10.0 +/- 1.1) ratings (p = 0.001), whereas Claude outperformed the other chatbots in its DISCERN scores (47.6 +/- 1.2) (p = 0.001). PEMAT-P understandability was the lowest in GPT-4 (53.2 +/- 2.0), and actionability was the highest in Claude (61.8 +/- 3.5) (p = 0.001).Conclusion: GPT-4 had the most complex language structure of the five chatbots, making it the most difficult to read and comprehend, whereas Grok was the simplest. Claude had the best KS text quality. Chatbot technology can improve healthcare material and make it easier to grasp.en10.1089/end.2024.0474info:eu-repo/semantics/closedAccessartificial intelligenceClaudeGPT-4Google PaLMGrokMistralkidney stoneArticleN/AWOS:0013062765000012-s2.0-8520352300339212674Q1