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Evaluating Chat Generative Pretrained Transformer (GPT-4o) Problem-Solving Performance in the Japan Certificate
1Faculty of Engineering, Shonan Institute of Technology, Fujisawa, JPN.
ChatGPT (GPT-4o) shows potential in medical engineering but struggles with complex problem-solving on the Certificate Examination for Biomedical Engineering class 1. Its current knowledge is insufficient for universal accuracy in this field.
Area of Science:
- Medical Engineering
- Artificial Intelligence in Healthcare
Background:
- The Certificate Examination for Biomedical Engineering class 1 (CEBM1) assesses medical device maintenance and safety expertise.
- ChatGPT (GPT-4o) is increasingly applied across various professional domains, including medical engineering.
Purpose of the Study:
- To evaluate the performance of ChatGPT (GPT-4o) on the CEBM1.
- To compare AI capabilities against human-level expectations in biomedical engineering assessment.
Main Methods:
- 171 Japanese CEBM1 questions (26th-28th exams) were input into ChatGPT (GPT-4o).
- Performance was assessed based on question difficulty (fundamental, applied, problem-solving).
- No prompt optimizations were applied; responses were compared to correct answers.
Main Results:
- ChatGPT achieved scores of 68.4% (fundamental), 57.9% (applied), and 59.6% (problem-solving).
- The 60% passing threshold was only met for the 28th examination.
- Incorrect answers stemmed primarily from knowledge gaps or inaccuracies, with some instances of misunderstanding and hallucination.
Conclusions:
- ChatGPT demonstrates foundational medical engineering knowledge but lacks universal accuracy.
- Current AI capabilities are insufficient for fully addressing complex medical device safety and maintenance challenges.
- Further development is needed for AI to reliably pass specialized professional examinations in medical engineering.
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