Prevalence of Machine Learning in Craniofacial Surgery.

Journal: The Journal of craniofacial surgery
Published Date: Jun 1, 2020

Abstract

Machine learning (ML) revolves around the concept of using experience to teach computer-based programs to reliably perform specific tasks. Healthcare setting is an ideal environment for adaptation of ML applications given the multiple specific tasks that could be allocated to computer programs to perform. There have been several scoping reviews published in literature looking at the general acceptance and adaptability of surgical specialities to ML applications, but very few focusing on the application towards craniofacial surgery. This study aims to present a detailed scoping review regarding the use of ML applications in craniofacial surgery.

Authors

  • Martin L Mak
    Hospital for Sick Children.
  • Sultan Z Al-Shaqsi
    Plastic and Reconstructive Surgery, University of Toronto, Toronto, Canada.
  • John Phillips
    Department of Molecular and Medical Pharmacology, University of California, Los Angeles, Los Angeles, CA, USA.

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