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Paper Abstract and Keywords
Presentation 2025-01-23 12:30
Analysis of Response of Large Language Model to the Difficult Medical Engineering Examinations
Kai Ishida (SIT) MICT2024-54 MBE2024-35
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, large language models (LLM) have quickly gained popularity in medical applications. It has been reported that LLM has potential to pass some national medical and healthcare licenses. However, the benchmark of applied knowledge and problem-solving ability of LLMs in the field of medical engineering is unknown. In this study, we evaluated the performance of ChatGPT (GPT-4o) on 26th to 28th certificate examination for biomedical engineering (Class1). The average correct answer rate for basic, applied and problem solving questions were 68.4%, 57.9% and 59.6%, respectively. The average correct answer rate for multiple choice, written, calculations and image-base questions were 68.4%, 59.7%, 55.9% and 57.1%, respectively. In essay exam, ChatGPT generated an answer sentence with a predetermined number of characters in all exams.
Keyword (in Japanese) (See Japanese page) 
(in English) Large language model / ChatGPT / Certificate examination for biomedical engineering (Class1) / Medical education / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 351, MICT2024-54, pp. 30-33, Jan. 2025.
Paper # MICT2024-54 
Date of Issue 2025-01-16 (MICT, MBE) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF MICT2024-54 MBE2024-35

Conference Information
Committee MBE MICT IEE-MBE  
Conference Date 2025-01-23 - 2025-01-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyushu Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MICT 
Conference Code 2025-01-MBE-MICT-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Analysis of Response of Large Language Model to the Difficult Medical Engineering Examinations 
Sub Title (in English)  
Keyword(1) Large language model  
Keyword(2) ChatGPT  
Keyword(3) Certificate examination for biomedical engineering (Class1)  
Keyword(4) Medical education  
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1st Author's Name Kai Ishida  
1st Author's Affiliation Shonan Institute of Technology (SIT)
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Speaker Author-1 
Date Time 2025-01-23 12:30:00 
Presentation Time 25 minutes 
Registration for MICT 
Paper # MICT2024-54, MBE2024-35 
Volume (vol) vol.124 
Number (no) no.351(MICT), no.352(MBE) 
Page pp.30-33 
#Pages 4 
Date of Issue 2025-01-16 (MICT, MBE) 

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