Artificial Intelligence Chatbots' Understanding of the Risks and Benefits of Computed Tomography and Magnetic Resonance Imaging Scenarios.

Journal: Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Published Date: Jan 6, 2024

Abstract

PURPOSE: Patients may seek online information to better understand medical imaging procedures. The purpose of this study was to assess the accuracy of information provided by 2 popular artificial intelligence (AI) chatbots pertaining to common imaging scenarios' risks, benefits, and alternatives.

Authors

  • Nikhil S Patil
    Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada.
  • Ryan S Huang
    Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
  • Scott Caterine
    Department of Radiology, McMaster University, Hamilton, Ontario, Canada.
  • Jason Yao
    Department of Radiology, University of Ottawa Faculty of Medicine, 501 Smyth Road, Box 232, Ottawa, ON, K1H 8L6, Canada. jason.yao21@gmail.com.
  • Natasha Larocque
    Associate Program Director, McMaster Diagnostic Radiology Program, Competency by Design lead, McMaster Diagnostic Radiology Program, Simulation lead, McMaster Diagnostic Radiology Program, and Assistant Professor of Radiology, Department of Radiology, McMaster University, Hamilton, Ontario, Canada. Electronic address: natasha.larocque@medportal.ca.
  • Christian B van der Pol
    Department of Radiology, McMaster University, Hamilton, Ontario, Canada.
  • Euan Stubbs
    Department of Radiology, McMaster University, Hamilton, Ontario, Canada; Department of Diagnostic Imaging, St Joseph's Hospital, Hamilton, Ontario, Canada. Electronic address: estubbs@stjosham.on.ca.

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