Can machine learning predict resecability of a peritoneal carcinomatosis?

Journal: Surgical oncology
Published Date:

Abstract

BACKGROUND: Approximately 20% of initially eligible patients in a HIPEC procedure eventually underwent a simple surgical exploration. These procedures are called 'open & close' (O & C) representing up to 48% of surgery. The objective of this study was to predict the resecability of peritoneal carcinomatosis using a machine-learning model for decision-making support, for eligible patients of HIPEC.

Authors

  • A Maubert
    General and Oncology Surgery Unit, Archet 2 Hospital, University Hospital of Nice, Nice, France. Electronic address: maubert.a@chu-nice.fr.
  • L Birtwisle
    General and Oncology Surgery Unit, Archet 2 Hospital, University Hospital of Nice, Nice, France.
  • J L Bernard
    General and Oncology Surgery Unit, Archet 2 Hospital, University Hospital of Nice, Nice, France.
  • E Benizri
    General and Oncology Surgery Unit, Archet 2 Hospital, University Hospital of Nice, Nice, France.
  • J M Bereder
    General and Oncology Surgery Unit, Archet 2 Hospital, University Hospital of Nice, Nice, France.