Published on in Vol 26 (2024)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52880, first published .
Machine Learning Approaches for the Image-Based Identification of Surgical Wound Infections: Scoping Review

Machine Learning Approaches for the Image-Based Identification of Surgical Wound Infections: Scoping Review

Machine Learning Approaches for the Image-Based Identification of Surgical Wound Infections: Scoping Review

Juan Pablo Tabja Bortesi   1 , HBSc ;   Jonathan Ranisau   1 , MASc ;   Shuang Di   1, 2 , MSc ;   Michael McGillion   3 , PhD ;   Laura Rosella   2 , PhD ;   Alistair Johnson   4 , DPhil ;   PJ Devereaux   3 , PhD ;   Jeremy Petch   1, 3, 5, 6 , BA, MA, PhD

1 Centre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, ON, Canada

2 Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada

3 Population Health Research Institute, Hamilton, ON, Canada

4 SickKids Research Institute, Toronto, ON, Canada

5 Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada

6 Division of Cardiology, McMaster University, Hamilton, ON, Canada

Corresponding Author:

  • Jeremy Petch, BA, MA, PhD
  • Centre for Data Science and Digital Health
  • Hamilton Health Sciences
  • 175 Longwood Road South
  • Suite 207
  • Hamilton, ON, L8P 0A1
  • Canada
  • Phone: 1 9055212100
  • Email: petchj@hhsc.ca