Page 61 - Read Online

Ganesan et al. Art Int Surg 2024;4:364-75 Artificial
DOI: 10.20517/ais.2024.68
Intelligence Surgery

Review Open Access

A review of artificial intelligence in wound care

1,2
3
3
Ovya Ganesan , Miranda Xiao Morris , Lifei Guo , Dennis Orgill 1,4
1
Division of Plastic and Reconstructive Surgery, Brigham and Women’s Hospital, Boston, MA 02115, USA.
2
Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.
3
Plastic and Reconstructive Surgery, Lahey Hospital and Medical Center, Boston, MA 01805, USA.
4
Harvard Medical School, Boston, MA 02115, USA.
Correspondence to: Dr. Dennis Orgill, Plastic Surgery Department, Brigham and Women’s Hospital, 75 Francis Street, Boston,
MA 02115, USA. E-mail: dorgill@bwh.harvard.edu
How to cite this article: Ganesan O, Morris MX, Guo L, Orgill D. A review of artificial intelligence in wound care. Art Int Surg
2024;4:364-75. https://dx.doi.org/10.20517/ais.2024.68
Received: 15 Aug 2024 First Decision: 8 Oct 2024 Revised: 21 Oct 2024 Accepted: 28 Oct 2024 Published: 4 Nov 2024

Academic Editor: Andrew Gumbs Copy Editor: Pei-Yun Wang Production Editor: Pei-Yun Wang

Abstract
Our aging population, diabetes, and obesity have fueled the growth of chronic wounds seen throughout the world.
Often, wounds are a marker of poor health that leads to increased mortality rates. However, the diagnosis and
treatment of these wounds are challenging. Incorrectly differentiating between chronic wounds and other complex
conditions can lead to adverse events. Artificial intelligence (AI) has been shown to offer some early benefits, and
we hypothesized that it may enhance wound care but also carry some notable risks. We performed a detailed
search using PubMed, Scopus, Cumulated Index in Nursing and Allied Health Literature, and Web of Science for AI
applications in wound care. AI was found to be applied to wound diagnosis and characterization, wound monitoring
for tissue change, daily therapy, and prevention and prognostics. AI made for more efficient and accurate wound
assessments, less painful assessments of chronic wounds, more personalized treatment, and improved prognostic
prediction capabilities. AI also allowed for more precise at-home observation and care, facilitating earlier wound
treatment as needed. Challenges associated with AI included how to best allocate AI-assisted technologies
equitably, how to safely maintain patient data, and how to diversify datasets for algorithm training. Because the
algorithms are not transparent, validating findings may be challenging. AI presents a powerful tool in several
aspects of advanced wound care and has the potential to improve diagnoses, accelerate healing, reduce pain, and
improve the cost-effectiveness of wound care. More research needs to be done into how to best incorporate AI
into daily clinical practice while keeping clinicians aware of the potential risks of using these evolving technologies.

Keywords: Artificial intelligence, wound healing, wound care, hard-to-heal wounds, chronic wounds, ulcers

© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
indicate if changes were made.

www.oaepublish.com/ais