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Health·The Trace·Dual reading·Published 2026-08-10

AI-generated responses to EAU erectile dysfunction guideline questions

Source article: Quality assessment of artificial intelligence responses in erectile dysfunction: a comparative study based on EAU recommendations

Abstract: Artificial intelligence (AI)-based language models are increasingly explored as tools for interpreting and applying clinical guideline recommendations. In urology, the European Association of Urology (EAU) recently introduced a guideline-specific chatbot; however, its comparative performance relative to contemporary general-purpose large language models (LLMs) remains unclear. In this structured comparative study, five AI systems-the EAU Guidelines Bot, ChatGPT-5, Gemini 2.5 Pro, Copilot - Smart GPT-5, and Perpl…

TRV-2026-0727Peer-reviewedPermanent record — cite & verify
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Quality assessment of artificial intelligence responses in erectile dysfunction: a comparative study based on EAU recommendations

"Natalie Korotaeva: Chatbot UX" by uxproaustria is licensed under CC BY 2.0. To view a copy of this license, visit https://creativecommons.org/licenses/by/2.0/.

The quick read

On 2026-08-07, a peer-reviewed comparative study tested five AI systems including the EAU Guidelines Bot, ChatGPT-5, Gemini 2.5 Pro, Copilot - Smart GPT-5, and Perplexity Pro on 13 questions drawn from strongly recommended EAU erectile dysfunction statements. Three senior reviewers rated each answer for relevance, clarity, structure, clinical utility, and factual accuracy.

The results matter because they show both specialized and general models can approximate guideline-based answers in controlled scenarios, yet performance gaps and domain variability mean they cannot replace clinical judgment. Uncertainty remains about how these scores translate to real patient counseling, safety, and decision-making outside structured testing.

Main points
  • Study evaluated 5 AI systems using 13 clinical questions derived from strongly recommended EAU erectile dysfunction guideline statements.
  • Three senior reviewers scored responses on relevance, clarity, structure, clinical utility, and factual accuracy using a 5-point Likert scale.
  • Inter-rater reliability calculated with ICC(2,k) and model differences tested with Friedman test followed by Holm-adjusted Wilcoxon comparisons.
Gain

Guideline-specific and general-purpose LLMs produced responses broadly consistent with EAU erectile dysfunction recommendations, with Gemini 2.5 Pro and EAU Guidelines Bot achieving the highest composite scores.

Problem

Performance varied significantly across models and domains, with Copilot and Perplexity scoring lower and greater inconsistency in clarity, structure, and clinical utility.

The rundown

The comparison used 13 questions directly from strongly recommended statements in the EAU erectile dysfunction guidelines, with the primary outcome defined as the mean of five domain scores. Significant differences were found across all domains with p < 0.001.

Domain-level results showed top models maintained median scores >=4 for factual accuracy, while ChatGPT-5 scored 4.27 (4.07-4.47) in the middle range, indicating uneven performance on structure and clinical utility despite overall consistency.

What this doesn’t fix

Findings are limited to structured guideline-derived scenarios and have not been validated in real-world clinical decision-making.

Sources

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