ArticleWorld journal of urology2024
Performance of ChatGPT-3.5 and ChatGPT-4 on the European Board of Urology (EBU) exams: a comparative analysis.
Article in World journal of urology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy of Large Language Models When Answering Clinical Research Questions: Systematic Review and Network Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Bloom's taxonomy-based comparison of artificial intelligence and dental students in restorative dentistry.BMC medical education · 2026Article
- Assessing multiple chatGPT versions on novel content in the Taiwan urology board examination: accuracy, speed, and domain-specific performance.World journal of urology · 2026Article
- Comparative analysis of the effectiveness of microsoft copilot artificial intelligence chatbot and google search in answering patient inquiries about infertility: evaluating readability, understandability, and actionability.International journal of impotence research · 2025Article
- Evaluating ChatGPT's role in urological counseling and clinical decision support.World journal of urology · 2025Article
- Which current chatbot is more competent in urological theoretical knowledge? A comparative analysis by the European board of urology in-service assessment.World journal of urology · 2025Article
- Clinical decision-making in neonatal gastrointestinal surgical emergencies: comparison between ChatGPT and human clinicians.World journal of pediatric surgery · 2025Article
- Article
- Letter to the editor for the article "Performance of ChatGPT-3.5 and ChatGPT-4 on the European Board of Urology (EBU) exams: a comparative analysis".World journal of urology · 2024Article
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5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveIn the transformative era of artificial intelligence, its integration into various spheres, especially healthcare, has been promising. The objective of this study was to analyze the performance of ChatGPT, as open-source Large Language Model (LLM), in its different versions on the recent European Board of Urology (EBU) in-service assessment questions. DESIGN AND
settingWe asked multiple choice questions of the official EBU test books to ChatGPT-3.5 and ChatGPT-4 for the following exams: exam 1 (2017-2018), exam 2 (2019-2020) and exam 3 (2021-2022). Exams were passed with ≥60% correct answers.
resultsChatGPT-4 provided significantly more correct answers in all exams compared to the prior version 3.5 (exam 1: ChatGPT-3.5 64.3% vs. ChatGPT-4 81.6%; exam 2: 64.5% vs. 80.5%; exam 3: 56% vs. 77%, p < 0.001, respectively). Test exam 3 was the only exam ChatGPT-3.5 did not pass. Within the different subtopics, there were no significant differences of provided correct answers by ChatGPT-3.5. Concerning ChatGPT-4, the percentage in test exam 3 was significantly decreased in the subtopics Incontinence (exam 1: 81.6% vs. exam 3: 53.6%; p = 0.026) and Transplantation (exam 1: 77.8% vs. exam 3: 0%; p = 0.020).
conclusionOur findings indicate that ChatGPT, especially ChatGPT-4, has the general ability to answer complex medical questions and might pass FEBU exams. Nevertheless, there is still the indispensable need for human validation of LLM answers, especially concerning health care issues.
Indexed as
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39060792What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.