Development of a Method for Clinical Evaluation of Artificial Intelligence-Based Digital Wound Assessment Tools.

Journal: JAMA network open
Published Date: May 3, 2021

Abstract

IMPORTANCE: Accurate assessment of wound area and percentage of granulation tissue (PGT) are important for optimizing wound care and healing outcomes. Artificial intelligence (AI)-based wound assessment tools have the potential to improve the accuracy and consistency of wound area and PGT measurement, while improving efficiency of wound care workflows.

Authors

  • Raelina S Howell
    Department of Surgery, NYU Langone Hospital Long Island, Mineola, New York.
  • Helen H Liu
    Department of Surgery, NYU Langone Hospital Long Island, Mineola, New York.
  • Aziz A Khan
    Department of Surgery, NYU Langone Hospital Long Island, Mineola, New York.
  • Jon S Woods
    Department of Surgery, NYU Langone Hospital Long Island, Mineola, New York.
  • Lawrence J Lin
    NYU Kimmel Hyperbaric and Advanced Wound Healing Center, New York, New York.
  • Mayur Saxena
    Droice Labs, New York, New York.
  • Harshit Saxena
    Droice Labs, New York, New York.
  • Michael Castellano
    Department of Surgery, NYU Langone Hospital Long Island, Mineola, New York.
  • Patrizio Petrone
    Department of Surgery, NYU Langone Hospital Long Island, Mineola, New York.
  • Eric Slone
    Department of Surgery, NYU Langone Hospital Long Island, Mineola, New York.
  • Ernest S Chiu
    NYU Kimmel Hyperbaric and Advanced Wound Healing Center, New York, New York.
  • Brian M Gillette
    Department of Surgery, NYU Langone Hospital Long Island, Mineola, New York.
  • Scott A Gorenstein
    Department of Surgery, NYU Langone Hospital Long Island, Mineola, New York.

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