The accuracy of artificial intelligence ChatGPT in oncology examination questions Journal Article


Authors: Chow, R.; Hasan, S.; Zheng, A.; Gao, C.; Valdes, G.; Yu, F.; Chhabra, A.; Raman, S.; Choi, J. I.; Lin, H.; Simone, C. B. 2nd
Article Title: The accuracy of artificial intelligence ChatGPT in oncology examination questions
Abstract: The aim of this study is to assess the accuracy of Chat Generative Pretrained Transformer (ChatGPT) in response to oncology examination questions in the setting of one-shot learning. Consecutive national radiation oncology in-service multiple-choice examinations were collected and inputted into ChatGPT 4o and ChatGPT 3.5 to determine ChatGPT's answers. ChatGPT's answers were then compared with the answer keys to determine whether ChatGPT correctly or incorrectly answered each question and to determine if improvements in responses were seen with the newer ChatGPT version. A total of 600 consecutive questions were inputted into ChatGPT. ChatGPT 4o answered 72.2% questions correctly, whereas 3.5 answered 53.8% questions correctly. There was a significant difference in performance by question category (P < .01). ChatGPT performed poorer with respect to knowledge of landmark studies and treatment recommendations and planning. ChatGPT is a promising technology, with the latest version showing marked improvement. Although it still has limitations, with further evolution, it may be considered a reliable resource for medical training and decision making in the oncology space. © 2024 American College of Radiology
Keywords: pathology; oncology; medical education; education; radiation oncology; artificial intelligence; medical oncology; anatomy; cancer epidemiology; decision making; educational measurement; radiobiology; health physics; procedures; humans; human; article; one-shot learning; chatgpt; examination questions; anatomical landmark
Journal Title: Journal of the American College of Radiology
Volume: 21
Issue: 11
ISSN: 1546-1440
Publisher: Elsevier Science, Inc.  
Date Published: 2024-11-01
Start Page: 1800
End Page: 1804
Language: English
DOI: 10.1016/j.jacr.2024.07.011
PUBMED: 39098369
PROVIDER: scopus
DOI/URL:
Notes: Article -- Source: Scopus
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  1. Charles Brian Simone
    190 Simone