Machine Learning for Predicting Complications in Head and Neck Microvascular Free Tissue Transfer.

Journal: The Laryngoscope
Published Date: Dec 1, 2020

Abstract

OBJECTIVES/HYPOTHESIS: Machine learning (ML) is a type of artificial intelligence wherein a computer learns patterns and associations between variables to correctly predict outcomes. The objectives of this study were to 1) use a ML platform to identify factors important in predicting surgical complications in patients undergoing head and neck free tissue transfer, and 2) compare ML outputs to traditionally employed logistic regression models.

Authors

  • Eric J Formeister
    Department of Otolaryngology-Head and Neck Surgery, University of California-San Francisco School of Medicine, San Francisco, California, U.S.A.
  • Rachel Baum
    Department of Environmental Sciences and Engineering, University of North Carolina School of Public Health, Chapel Hill, North Carolina, U.S.A.
  • P Daniel Knott
    Division of Facial Plastic & Reconstructive Surgery, Department of Otolaryngology, University of California-San Francisco, San Francisco, CA, USA.
  • Rahul Seth
    Department of Otolaryngology-Head and Neck Surgery, University of California-San Francisco School of Medicine, San Francisco, California, U.S.A.
  • Patrick Ha
    Department of Otolaryngology-Head and Neck Surgery, University of California-San Francisco School of Medicine, San Francisco, California, U.S.A.
  • William Ryan
    Department of Otolaryngology-Head and Neck Surgery, University of California-San Francisco School of Medicine, San Francisco, California, U.S.A.
  • Ivan El-Sayed
    Department of Otolaryngology-Head and Neck Surgery, University of California-San Francisco School of Medicine, San Francisco, California, U.S.A.
  • Jonathan George
    Department of Otolaryngology-Head and Neck Surgery, University of California-San Francisco School of Medicine, San Francisco, California, U.S.A.
  • Andrew Larson
    Department of Otolaryngology-Head and Neck Surgery, University of California-San Francisco School of Medicine, San Francisco, California, U.S.A.
  • Karolina Plonowska
    Department of Otolaryngology-Head and Neck Surgery, University of California-San Francisco School of Medicine, San Francisco, California, U.S.A.
  • Chase Heaton
    Department of Otolaryngology-Head and Neck Surgery, University of California-San Francisco School of Medicine, San Francisco, California, U.S.A.

Keywords

External Resources

Popular Topics
Recent Journals