Accepted for/Published in: JMIR Medical Education
Date Submitted: Mar 11, 2023
Open Peer Review Period: Mar 11, 2023 - May 25, 2023
Date Accepted: Sep 21, 2023
(closed for review but you can still tweet)
Assessing the Performance of ChatGPT in Medical Biochemistry Using Clinical Case Vignettes
ABSTRACT
Background:
ChatGPT has gained global attention recently owing to its high performance in generating wide range of information and retrieving any kind of data instantaneously. ChatGPT has also been tested for the United States Medical Licensing Examination (USMLE) and has successfully cleared the medical exam. Thus, its usability in medical education is now one of the key discussions worldwide.
Objective:
The objective of this study is to evaluate the performance of ChatGPT in Medical biochemistry using clinical case vignettes.
Methods:
We evaluated the performance of ChatGPT in Medical biochemistry using 10 clinical case vignettes. Clinical case vignettes were randomly selected and typed onto ChatGPT along with the options. We tested the responses for each clinical case twice. The answers generated by ChatGPT were saved and checked using our reference material.
Results:
ChatGPT generated correct answers for 4 questions in the first attempt. For the other cases, there was difference in responses generated by ChatGPT in the first and second attempt. But to our surprise, for Case 3, different answers were given with multiple attempts. We believe this to have happened owing to the complexity of the case.
Conclusions:
According to the findings of our study, ChatGPT may not be considered an accurate information provider that can be applied in medical education to improve learning and assessment. Although, AI has the capability to transform medical education, we emphasize on the validation of such data produced by such AI systems for correctness and dependability before it could be put into practice.
Citation
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Copyright
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