ArticleInternational braz j urol : official journal of the Brazilian Society of Urology
Performance of ChatGPT and DeepSeek in the Management of Postprostatectomy Urinary Incontinence
Article in International braz j urol : official journal of the Brazilian Society of Urology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Artificial intelligence advancements for orthopaedic clinical reasoning: longitudinal assessment of newer models (ChatGPT-5, Grok-3, Gemini 2.5 Flash) compared to clinicians.Archives of orthopaedic and trauma surgery · 2026Article
- Applications of DeepSeek in Medicine: Bibliometric Analysis and Scoping Review.Journal of medical Internet research · 2026Article
- Comparison of the performance of large language models in answering patient questions related to cataract.iScience · 2026Article
- Estimation of IPSS and OABSS scores using ChatGPT-4o: a comparative validation study in Korea.BMC urology · 2026Article
- Evaluating AI-generated patient education materials for endometrial cancer surgery: a comparative analysis of response quality, reliability, and readability between ChatGPT and DeepSeek models.Frontiers in public health · 2026Article
- Large Language Models and the "Centaur Model" in Urological Training in Latin America.International braz j urol : official journal of the Brazilian Society of UrologyArticle
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10 authors.
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Abstract
purposeArtificial intelligence (AI) continues to evolve as a tool in clinical decision support. Large language models (LLMs), such as ChatGPT and DeepSeek, are increasingly used in medicine to provide fast, accessible information. This study aimed to compare the performance of ChatGPT and DeepSeek in generating recommendations for the management of postprostatectomy urinary incontinence (PPUI), based on the AUA/SUFU guideline. MATERIALS AND
methodsA total of 20 questions (10 conceptual and 10 case-based) were developed by three urologists with expertise in PPUI, following the AUA/SUFU guideline. Each question was submitted in English using zero-shot prompting to ChatGPT-4o and DeepSeek R1. Responses were limited to 200 words and graded independently as correct (1 point), partially correct (0.5), or incorrect (0). Total and domain-specific scores were compared.
resultsChatGPT achieved 19 out of 20 points (95.0%), while DeepSeek scored 14.5 (72.5%; p = 0.031). In conceptual questions, scores were 9.0 (ChatGPT) and 8.0 (DeepSeek; p = 0.50). In case-based scenarios, ChatGPT scored 10.0 versus 6.5 for DeepSeek (p = 0.08). ChatGPT outperformed DeepSeek across all guideline domains. DeepSeek made critical errors in the treatment domain, such as recommending a male sling for radiated patients.
conclusionChatGPT demonstrated superior performance in providing guideline-based recommendations for PPUI. However, both models should be used under expert supervision, and future research is needed to optimize their safe integration into clinical workflows.
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