Using ChatGPT to evaluate cancer myths and misconceptions: artificial intelligence and cancer information.

Journal: JNCI cancer spectrum
Published Date:

Abstract

Data about the quality of cancer information that chatbots and other artificial intelligence systems provide are limited. Here, we evaluate the accuracy of cancer information on ChatGPT compared with the National Cancer Institute's (NCI's) answers by using the questions on the "Common Cancer Myths and Misconceptions" web page. The NCI's answers and ChatGPT answers to each question were blinded, and then evaluated for accuracy (accurate: yes vs no). Ratings were evaluated independently for each question, and then compared between the blinded NCI and ChatGPT answers. Additionally, word count and Flesch-Kincaid readability grade level for each individual response were evaluated. Following expert review, the percentage of overall agreement for accuracy was 100% for NCI answers and 96.9% for ChatGPT outputs for questions 1 through 13 (ĸ = ‒0.03, standard error = 0.08). There were few noticeable differences in the number of words or the readability of the answers from NCI or ChatGPT. Overall, the results suggest that ChatGPT provides accurate information about common cancer myths and misconceptions.

Authors

  • Skyler B Johnson
    Department of Radiation Oncology, University of Utah School of Medicine, Huntsman Cancer Institute, Salt Lake City, UT, USA.
  • Andy J King
    Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, USA.
  • Echo L Warner
    Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, USA.
  • Sanjay Aneja
    Yale University, New Haven, Connecticut.
  • Benjamin H Kann
    Artificial Intelligence in Medicine (AIM) Program, Harvard Medical School, Boston, Massachusetts, USA.
  • Carma L Bylund
    Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA.