Artificial intelligence for prediction of treatment outcomes in breast cancer: Systematic review of design, reporting standards, and bias.

Journal: Cancer treatment reviews
Published Date: May 19, 2022

Abstract

BACKGROUND: Artificial intelligence (AI) has the potential to personalize treatment strategies for patients with cancer. However, current methodological weaknesses could limit clinical impact. We identified common limitations and suggested potential solutions to facilitate translation of AI to breast cancer management.

Authors

  • 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.
  • Marisa Cobanaj
    Department of Electronics Informatics and Bioengineering, Polytechnic University of Milan, Milan, Italy.
  • Federica Marian
    DaVinci Healthcare, Milan, Italy.
  • Edward C Dee
    Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Maxwell R Lloyd
    Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA.
  • Sara Marcu
    S.A.T.E. Systems and Advanced Technologies Engineering, Venice, Italy.
  • Andra Dombrovschi
    Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy.
  • Giorgio P Biondetti
    OM1, Inc., Boston, MA, USA.
  • Felipe Batalini
    Women's Cancer Program, Mayo Clinic Cancer Center, Phoenix, AZ, USA.
  • Leo A Celi
    Beth Israel Deaconess Medical Center, Pulmonary Division and Harvard Medical School, Boston, MA 02215, USA.
  • Giuseppe Curigliano
    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.

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