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Comparative Evaluation of Advanced Reasoning Models for Clinical Decision Support in Urology
Ning He1, Yang Wang1, Xinhong Hu1
1Department of Urology, Hanzhong Central Hospital, Hanzhong, China.
Urologia Internationalis
|March 23, 2026
Summary
Advanced reasoning models demonstrate high accuracy on urology questions, outperforming experienced urologists. ChatGPT O4-mini shows particular promise as a clinical assistant due to its speed and accuracy.
Area of Science:
- Artificial Intelligence in Medicine
- Medical Education Technology
- Clinical Decision Support Systems
Background:
- The integration of advanced reasoning models into clinical practice requires rigorous evaluation.
- Assessing artificial intelligence (AI) performance against human expertise is crucial for understanding their potential and limitations.
- Urology, with its complex clinical scenarios, presents a valuable domain for benchmarking AI capabilities.
Purpose of the Study:
- To compare the performance of five leading AI reasoning models on urology-focused multiple-choice questions.
- To benchmark AI accuracy, response efficiency, and agreement against medical students and experienced urologists.
- To evaluate the potential of AI as clinical assistants in urology.
Main Methods:
- Five AI models (DeepSeek-R1, ChatGPT O4-mini, Gemini 2.5 Pro, Claude 3.7 Sonnet, Grok 3) were tested on 434 urology questions from the MedQA dataset.
- AI accuracy was measured against reference answers, with API response times and connection failures recorded.
- Human performance was assessed using 20 senior medical students and 20 experienced urologists, with group majority votes serving as baselines.
Main Results:
- All AI models achieved high accuracy (86.9-93.3%), with DeepSeek-R1, ChatGPT O4-mini, and Gemini 2.5 Pro showing superior performance.
- AI models demonstrated significantly higher accuracy than experienced urologists (p < 0.001), while students' performance was comparable to urologists.
- ChatGPT O4-mini exhibited the fastest median API response time (5.03 s), outperforming human task completion times (15.87-17.57 s).
- Moderate-to-substantial agreement (Fleiss' κ = 0.685) was observed across AI models and human baselines.
Conclusions:
- Modern AI reasoning models show strong accuracy and efficiency in urology-specific assessments.
- These AI models show potential as valuable clinical assistants, provided appropriate human oversight is maintained.
- ChatGPT O4-mini's rapid response time and high accuracy suggest its suitability for time-sensitive clinical workflows.
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