Characterizing the Increase in Artificial Intelligence Content Detection in Oncology Scientific Abstracts From 2021 to 2023.

Journal: JCO clinical cancer informatics
PMID: 38822755

Abstract

PURPOSE: Artificial intelligence (AI) models can generate scientific abstracts that are difficult to distinguish from the work of human authors. The use of AI in scientific writing and performance of AI detection tools are poorly characterized.

Authors

  • Frederick M Howard
    Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL, USA.
  • Anran Li
    Section of Hematology/Oncology, Department of Medicine, University of Chicago Medical Center, Chicago, IL, USA.
  • Mark F Riffon
    Center for Research and Analytics, American Society of Clinical Oncology, Alexandria, VA.
  • Elizabeth Garrett-Mayer
    Center for Research and Analytics, American Society of Clinical Oncology, Alexandria, VA.
  • Alexander T Pearson
    Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL, USA.

Keywords

External Resources

Popular Topics
Recent Journals