ArticleFrontiers in artificial intelligence2025
A multi-model longitudinal assessment of ChatGPT performance on medical residency examinations.
Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- A Rasch-based analysis comparing the performance of updated multimodal large language models and surgeons on the Japanese surgical specialist examination.Surgery today · 2026Article
- AI-Powered Clinical Decision Support in Dentistry: Comparative Evaluation of Large Language Models for Oral Medicine and Periodontal Diagnosis.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Transforming thyroid disease education: AI and virtual technologies in residency training.Frontiers in endocrinology · 2026Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: ChatGPT, a generative artificial intelligence, has potential applications in numerous fields, including medical education. This potential can be assessed through its performance on medical exams. Medical residency exams, critical for entering medical specialties, serve as a valuable benchmark. Materials and methods: This study aimed to assess the accuracy of ChatGPT-4 and GPT-4o in responding to 1,041 medical residency questions from Brazil, examining overall accuracy and performance across different medical areas, based on evaluations conducted in 2023 and 2024. The questions were classified into higher and lower cognitive levels according to Bloom's taxonomy. Additionally, questions answered incorrectly by both models were tested using the recent GPT models that use chain-of-thought reasoning (e.g., o1-preview, o3, o4-mini-high) with evaluations carried out in both 2024 and 2025. Results: GPT-4 achieved 81.27% accuracy (95% CI: 78.89-83.64%), while GPT-4o reached 85.88% (95% CI: 83.76-88.00%), significantly outperforming GPT-4 ( Conclusion: Artificial intelligence could be a beneficial tool in medical education, enhancing residency exam preparation, helping to understand complex topics, and improving teaching strategies. However, careful use of artificial intelligence is essential due to ethical concerns and potential limitations in both educational and clinical practice.
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Registered trials
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