Machine-learning-derived classifier predicts absence of persistent pain after breast cancer surgery with high accuracy.

Journal: Breast cancer research and treatment
Published Date: Sep 1, 2018

Abstract

BACKGROUND: Prevention of persistent pain following breast cancer surgery, via early identification of patients at high risk, is a clinical need. Supervised machine-learning was used to identify parameters that predict persistence of significant pain.

Authors

  • Jörn Lötsch
    Institute of Clinical Pharmacology, Goethe - University, Theodor Stern Kai 7, 60590 Frankfurt am Main, Germany.
  • Reetta Sipilä
    Pain Clinic, Department of Anaesthesiology, Intensive Care and Pain Medicine, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
  • Tiina Tasmuth
    Pain Clinic, Department of Anaesthesiology, Intensive Care and Pain Medicine, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
  • Dario Kringel
    Institute of Clinical Pharmacology, Goethe - University, Theodor - Stern - Kai 7, 60590, Frankfurt am Main, Germany.
  • Ann-Mari Estlander
    Pain Clinic, Department of Anaesthesiology, Intensive Care and Pain Medicine, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
  • Tuomo Meretoja
    Breast Surgery Unit, Comprehensive Cancer Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
  • Eija Kalso
    Pain Clinic, Department of Anaesthesiology, Intensive Care and Pain Medicine, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
  • Alfred Ultsch
    DataBionics Research Group, University of Marburg, Hans - Meerwein - Straße, 35032 Marburg, Germany.

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