ArticleHeliyon2024
Evaluating the performance of ChatGPT-3.5 and ChatGPT-4 on the Taiwan plastic surgery board examination.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Evaluation of DeepSeek-R1 and ChatGPT-4o on the Chinese national medical licensing examination: a multi-year comparative study.Scientific reports · 2026Article
- Token-splitting improves GPT-4.1 performance on plastic surgery exams: implications for AI-Assisted medical education.Medical education online · 2025Article
- Comparative performance of large language models in answering periodontology questions from the Turkish Dental Specialty Examination: a cross-sectional study on accuracy and coverage.BMC oral health · 2025Article
- Performance of the ChatGPT-5 Language Model in Solving a Specialty Examination in Balneology and Physical Medicine.Cureus · 2025Article
- Comparison of artificial intelligence systems in answering prosthodontics questions from the dental specialty exam in Turkey.Journal of dental sciences · 2025Article
- Performance of large language artificial intelligence models on solving restorative dentistry and endodontics student assessments.Clinical oral investigations · 2024Article
- Custom GPTs Enhancing Performance and Evidence Compared with GPT-3.5, GPT-4, and GPT-4o? A Study on the Emergency Medicine Specialist Examination.Healthcare (Basel, Switzerland) · 2024Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Chat Generative Pre-Trained Transformer (ChatGPT) is a state-of-the-art large language model that has been evaluated across various medical fields, with mixed performance on licensing examinations. This study aimed to assess the performance of ChatGPT-3.5 and ChatGPT-4 in answering questions from the Taiwan Plastic Surgery Board Examination. Methods: The study evaluated the performance of ChatGPT-3.5 and ChatGPT-4 on 1375 questions from the past 8 years of the Taiwan Plastic Surgery Board Examination, including 985 single-choice and 390 multiple-choice questions. We obtained the responses between June and July 2023, launching a new chat session for each question to eliminate memory retention bias. Results: Overall, ChatGPT-4 outperformed ChatGPT-3.5, achieving a 59 % correct answer rate compared to 41 % for ChatGPT-3.5. ChatGPT-4 passed five out of eight yearly exams, whereas ChatGPT-3.5 failed all. On single-choice questions, ChatGPT-4 scored 66 % correct, compared to 48 % for ChatGPT-3.5. On multiple-choice, ChatGPT-4 achieved a 43 % correct rate, nearly double the 23 % of ChatGPT-3.5. Conclusion: As ChatGPT evolves, its performance on the Taiwan Plastic Surgery Board Examination is expected to improve further. The study suggests potential reforms, such as incorporating more problem-based scenarios, leveraging ChatGPT to refine exam questions, and integrating AI-assisted learning into candidate preparation. These advancements could enhance the assessment of candidates' critical thinking and problem-solving abilities in the field of plastic surgery.
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Registered trials
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