Global disparities in artificial intelligence-based mammogram interpretation for breast cancer: A scientometric analysis of representation, trends, and equity.

Journal: European journal of cancer (Oxford, England : 1990)
PMID: 40209572

Abstract

BACKGROUND: Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer death among women worldwide. Artificial intelligence (AI) shows promise for improving mammogram interpretation, especially in resource-limited settings. However, concerns remain regarding the diversity of datasets and the representation of researchers in AI model development, which may affect the models' generalizability, fairness, and equity.

Authors

  • Isabele A Miyawaki
    Department of Medicine, Federal University of Parana, Curitiba, Parana, Brazil. Electronic address: isabeleayumi@ufpr.br.
  • Imon Banerjee
    Mayo Clinic, Department of Radiology, Scottsdale, AZ, USA.
  • Felipe Batalini
    Women's Cancer Program, Mayo Clinic Cancer Center, Phoenix, AZ, USA.
  • Carlos A Campello Jorge
    Department of Radiology, University of Michigan, Ann Arbor, MI, USA.
  • Leo A Celi
    Beth Israel Deaconess Medical Center, Pulmonary Division and Harvard Medical School, Boston, MA 02215, USA.
  • Marisa Cobanaj
    Department of Electronics Informatics and Bioengineering, Polytechnic University of Milan, Milan, Italy.
  • Edward C Dee
    Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Judy W Gichoya
    The Johns Hopkins Hospital, Department of Radiology, 601 N Caroline St, Room 4223, Baltimore, MD 21287 (S.K.); Cleveland Clinic, Department of Radiation Oncology, Cleveland, Ohio (H.E.); Emory University School of Medicine, Department of Radiology, Atlanta, Georgia (J.G.); University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania (C.E.K.).
  • Zaphanlene Kaffey
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Maxwell R Lloyd
    Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA.
  • Lucas McCullum
    Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA.
  • Sruthi Ranganathan
    Department of Medicine, University of Cambridge, Cambridge, United Kingdom.
  • Chiara Corti
    Division of New Drugs and Early Drug Development for Innovative Therapies, European Institute of Oncology, IRCCS, Milan, Italy; Department of Oncology and Haematology (DIPO), University of Milan, Milan, Italy. Electronic address: chiara.corti@ieo.it.

Keywords

External Resources

Popular Topics
Recent Journals