Optical Biopsy Using a Neural Network to Predict Gene Expression From Photos of Wounds.

Journal: The Journal of surgical research
Published Date: Nov 23, 2021

Abstract

BACKGROUND: The clinical characterization of the biological status of complex wounds remains a considerable challenge. Digital photography provides a non-invasive means of obtaining wound information and is currently employed to assess wounds qualitatively. Advances in machine learning (ML) image processing provide a means of identifying "hidden" features in pictures. This pilot study trains a convolutional neural network (CNN) to predict gene expression based on digital photographs of wounds in a canine model of volumetric muscle loss (VML).

Authors

  • Grant Schumaker
    Department of Surgery, University of Vermont, Burlington, Vermont.
  • Andrew Becker
  • Gary An
    Department of Surgery, University of Vermont, USA.
  • Stephen Badylak
    McGowan Institute of Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
  • Scott Johnson
    Medical College of Wisconsin, Milwaukee, WI, USA.
  • Peng Jiang
    Department of Joint Surgery, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong 250021, China.
  • Yoram Vodovotz
    Department of Surgery, University of Pittsburgh, Pittsburgh, PA, United States.
  • R Chase Cockrell
    Department of Surgery, University of Vermont, Burlington, Vermont. Electronic address: Robert.cockrell@med.uvm.edu.

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