Digital Health

Revolutionising Wound Care Management Through Artificial Intelligence

DOI https://doi.org/10.70302/jpsim.v5i1.2420
Received: 13 Oct 2023 Accepted: 30 Nov 2023 Published Online: 28 Feb 2024

Abstract

The management of wounds has been around for a long time. The traditional methods of wound care management were time-consuming, labour-intensive, and not efficient enough to cater to today's fast-moving world's needs. Integrating AI into wound care means greater efficiency, accuracy, and better outcomes. AI is an emerging healthcare technology that provides a unique opportunity to monitor chronic wounds by allowing doctors and nurses to capture high-quality images of wounds while enabling constant feedback to support early detection, diagnosis, and treatment. The computerised insight provided by the integration of AI steers a more personalised healing course, with healing times controlled based on various factors, such as wound type, size, and location. This insight builds into the multiple aspects of Artificial Intelligence that can best be used to track wounds' healing progress, signage of probable issues, and clinical hours spent by caregivers.

How to Cite This Article

Tariq G, Chughtai S. Revolutionising Wound Care Management Through Artificial Intelligence. J Pak Soc Intern Med. 2024;5(1):446–451. doi:10.70302/jpsim.v5i1.2420

⭳ Download PDF

Conflict of Interest

All authors declare no competing interests.

Disclosed in accordance with ICMJE and COPE guidelines.

Funding

No specific funding was received for this research.

Funder information follows the Crossref Funder Registry standard.

References

  1. Wang SH, Phillips P, Dong L. Artificial Intelligence–Enabled Chronic Wound Assessment Using a Mobile App-Based Clinical Decision Support System: Validation Study. JMIR Mhealth Uhealth 2021;9(5):e26380.
  2. Direkoglu C, Nixon MS. The application of digital image processing and analysis to chronic wound assessment. Chron Wound Care Manage Res. 2016; 3(1): 101-111.
  3. Wang, S.H., Tran, K.N., Abu Affan, M. et al. A Benchmark Study on Deep Learning for Wound Tissue Segmentation. NPJ Digital Med. 2022; https://doi.org/10.1038/s41746-022-00557-5 doi:10.1038/s41746-022-00557-5
  4. Chino D, Meloni M, Dessi A. Artificial intelligence: a future option for the diagnosis and management of lower extremity ulcers. Journal of Wound Care 2022; 31(Sup2a): S1-S26.

Reference list indexed for Google Scholar and ResearchGate. DOI links resolve via doi.org.

CC BY CC BY 4.0 This article is published under the Creative Commons Attribution 4.0 International License. May be shared and adapted with attribution. © 2024 Journal of Pakistan Society of Internal Medicine.