Present and future of machine learning in breast surgery: systematic review.

Journal: The British journal of surgery
Published Date: Oct 14, 2022

Abstract

BACKGROUND: Machine learning is a set of models and methods that can automatically detect patterns in vast amounts of data, extract information, and use it to perform decision-making under uncertain conditions. The potential of machine learning is significant, and breast surgeons must strive to be informed with up-to-date knowledge and its applications.

Authors

  • Chien Lin Soh
    School of Clinical Medicine, University of Cambridge, Cambridge, UK.
  • Viraj Shah
    Department of Medicine, Faculty of Medicine, Imperial College London, London, UK.
  • Arian Arjomandi Rad
    Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.
  • Robert Vardanyan
    Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.
  • Alina Zubarevich
    Department of Thoracic and Cardiovascular Surgery, West German Heart and Vascular Center Essen, University Hospital of Essen, University Duisburg-Essen, Hufelandstraße 55, 45122, Essen, Germany. Electronic address: alina.zubarevich@gmail.com.
  • Saeed Torabi
    Department of Anesthesiology and Intensive Care Medicine, University Hospital of Cologne, Cologne, Germany.
  • Alexander Weymann
    Department of Thoracic and Cardiovascular Surgery, West German Heart and Vascular Center Essen, University Hospital of Essen, University Duisburg-Essen, Hufelandstraße 55, 45122, Essen, Germany.
  • George Miller
    Research Unit, The Healthcare Leadership Academy, London, UK.
  • Johann Malawana
    Research Unit, The Healthcare Leadership Academy, London, UK.

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