Using AI to triage patients without clinically significant prostate cancer using biparametric MRI and PSA.

Journal: Abdominal radiology (New York)
Published Date:

Abstract

OBJECTIVES: To train and evaluate the performance of a machine learning triaging tool that identifies MRI negative for clinically significant prostate cancer and to compare this against non-MRI models.

Authors

  • Emerson P Grabke
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada.
  • Carolina A M Heming
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada.
  • Amit Hadari
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada.
  • Antonio Finelli
    Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
  • Sangeet Ghai
    Joint Department of Medical Imaging, Sinai Health System, University Health Network, University of Toronto, Toronto, Canada.
  • Katherine Lajkosz
    Department of Biostatistics, Princess Margaret Cancer Centre, Toronto, ON, Canada.
  • Babak Taati
  • Masoom A Haider
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.

Keywords

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