Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Analysis of AI-Generated Patient Education Guides for Urological Conditions: A Comparative Study Between ChatGPT and Gemini
0
Zitationen
2
Autoren
2025
Jahr
Abstract
Introduction Artificial intelligence (AI) chatbots are increasingly being used to create patient education guides (PEGs). However, there are gaps in the literature comparing the latest version in terms of readability, reliability, and similarity. The aim of this study was to compare PEGs generated by ChatGPT 5.1 (OpenAI, San Francisco, California, US) and Gemini 3 Pro (Google LLC, Mountain View, CA, USA) for five common urological conditions, kidney stone, urinary tract infection, urinary retention, erectile dysfunction, and benign prostatic hyperplasia, across these domains. Methods This cross-sectional study analysed PEGs generated by both AI chatbots for five common urological conditions using identical prompts. Readability was assessed using the Flesch Reading Ease Score and Flesch-Kincaid Grade Level. Reliability and similarity were assessed using a modified DISCERN score and Turnitin, respectively. Statistical comparison was performed using the Mann-Whitney U test. Results None of the evaluated characteristics showed a statistically significant difference between the PEGs generated by AI chatbots. Conclusion PEGs generated by both AI chatbots exceeded the recommended reading level, demonstrated limited originality, and showed moderate reliability, highlighting the need for professional oversight. Continued refinement of AI chatbots is necessary before integrating AI-generated PEGs into routine patient education.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.422 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.300 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.734 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.519 Zit.