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editorial
. 2019 Mar 18;16(2):311. doi: 10.1111/iwj.13108

Artificial intelligence and machine learning in wound care—The wounded machine!

Douglas Queen
PMCID: PMC7948899  PMID: 30887702

1.

Recently, I had the pleasure or daunting task of delivering a presentation on Machine Learning in Wound Care to a machine learning audience. It was during my research for this presentation that I thought of this editorial.

Many of our readers will have heard of the buzz words Artificial Intelligence (AI), Machine Learning (ML), and possibly even Deep Learning. But how many of you understand their meaning and, more importantly, their potential role in our wound care world.

One interesting fact is that the world of AI started before George Winter made his discovery regarding moist wound healing. The world of ML began its evolution around the same time as advanced dressing in the early 1980s. So, there are many parallels in the evolution of both subjects.

An AI technology that enables systems to learn without being programmed, ML is pushing the innovation boundaries across all industries, from health care to financial services. But what specifically is AI? AI is a constellation of technologies—from ML to natural language processing—that allows a machine to sense, comprehend, act, and learn.

So, why is it important? Well, AI will transform the relationship between people and technology, charging our creativity and skills. The future of AI promises a new era of disruption and productivity, where human ingenuity is enhanced by speed and precision.

Interesting I am sure, but what could this mean for wound care. Well, as you are aware, the evolution of the clinical specialty has been slow at best. One of the Achilles’ heels of the subject has been the lack of data or evidence. Often, many mention the need for “real‐world” data and how it would give a better handle on the practice of wound care. But its collection is difficult and expensive. Many have discussed the difficulties in clinical studies and also their expense for a relatively modest number of patients when compared with pharmaceuticals.

AI, through ML, can be the catalyst for the evolution of more informed wound care practice. Through the use of technology systems such as “apps,” our community can capture large volumes of data and then, through AI/ML techniques, begin to truly understand the areas of focus and change required to standardise the practice.

Through the use of data and DL techniques, wound care can be standardised through understanding and training. AI married to human intelligence will allow a more rapid standardisation and specialisation of wound care. This will be through two main areas: one, the actual ability to standardise practice through the many levels of care delivery and second, the ability, through the application of technology, to “up‐skill” its delivery even through less‐trained resources (eg, family or patient).

To date, AI has greatly changed the way in which we live and will continue to do so for the foreseeable future. One area that will have the most impact for those delivering wound care is the ultimate specialisation of this clinical area.

Do not dismiss technology and the ability of the machine to deliver this benefit. Embrace it and enjoy the impact it has on a better life for all of us, both as caregivers and as potential patients.


Articles from International Wound Journal are provided here courtesy of Wiley

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