Evaluation of responses to cardiac imaging questions by the artificial intelligence large language model ChatGPT.

Journal: Clinical imaging
PMID:

Abstract

PURPOSE: To assess ChatGPT's ability as a resource for educating patients on various aspects of cardiac imaging, including diagnosis, imaging modalities, indications, interpretation of radiology reports, and management.

Authors

  • Cynthia L Monroe
    College of Medicine, California Northstate University, 9700 W Taron Dr, Elk Grove, CA 95757, USA.
  • Yasser G Abdelhafez
    Department of Radiology, University of California, Davis Medical Center, 4860 Y St, Suite 3100, Sacramento, CA 95817, USA.
  • Kwame Atsina
    Division of Cardiovascular Medicine, University of California, Davis Medical Center, 4860 Y St, Suite 0200, Sacramento, CA 95817, USA.
  • Edris Aman
    Division of Cardiovascular Medicine, University of California, Davis Medical Center, 4860 Y St, Suite 0200, Sacramento, CA 95817, USA.
  • Lorenzo Nardo
    From the Department of Radiology and Biomedical Imaging (Y.D., J.H.S., H.T., R.H., N.W.J., T.P.C., M.S.A., C.M.A., S.C.B., R.R.F., S.Y.H., Y.S., R.A.H., M.H.P., B.L.F.) and Institute for Computational Health Sciences (J.H.S., M.G.K., H.T., D.L., K.A.Z., D.H.), University of California, San Francisco, 550 Parnassus Ave, San Francisco, CA 94143; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, Calif (Y.D.); and Department of Radiology, University of California, Davis, Sacramento, Calif (L.N.).
  • Mohammad H Madani
    Department of Radiology, School of Medicine, Stanford University, Stanford, CA, USA.