Development and Evaluation of a Machine Learning Prediction Model for Flap Failure in Microvascular Breast Reconstruction.

Journal: Annals of surgical oncology
Published Date: Sep 1, 2020

Abstract

BACKGROUND: Despite high success rates, flap failure remains an inherent risk in microvascular breast reconstruction. Identifying patients who are at high risk for flap failure would enable us to recommend alternative reconstructive techniques. However, as flap failure is a rare event, identification of risk factors is statistically challenging. Machine learning is a form of artificial intelligence that automates analytical model building. It has been proposed that machine learning can build superior prediction models when the outcome of interest is rare.

Authors

  • Anne C O'Neill
    Division of Plastic Surgery, Department of Surgery and Surgical Oncology, University Health Network, University of Toronto, Toronto, Canada. Anne.O'Neill@uhn.ca.
  • Dongyang Yang
    Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada.
  • Melissa Roy
    Division of Plastic Surgery, Department of Surgery and Surgical Oncology, University Health Network, University of Toronto, Toronto, Canada.
  • Stephanie Sebastiampillai
    Division of Plastic Surgery, Department of Surgery and Surgical Oncology, University Health Network, University of Toronto, Toronto, Canada.
  • Stefan O P Hofer
    Division of Plastic Surgery, Department of Surgery and Surgical Oncology, University Health Network, University of Toronto, Toronto, Canada.
  • Wei Xu
    College of Food and Bioengineering, Henan University of Science and Technology, Luoyang, 471023 China.

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