Case Study

How to innovate

Using AI to improve wound care

Where do new ideas come from? Collaboration is a good place to start when it comes to innovation, as we discovered when we talked to our medical client about their wound care provision.

Progress doesn’t always come from a clearly delineated problem. Sometimes it’s more a case of “here’s a few issues we’re facing, here’s where we think we’d like to end up in the future” and together we take it from there.

After learning more about our client’s business, we had a few ideas about how applying AI to how they currently worked could help them. We knew AI could help not just in the short term, improving the way customers used their products, but also to fast-track them to a future where they take the lead in delivering data-driven patient outcomes.

The idea involved building a bespoke AI application, which used computer vision/image recognition to help customers identify the right wound dressing to use. It would speed up diagnosis, identify appropriate treatment, and ultimately, improve patient outcomes. By working together – their industry knowledge along with our technical expertise – we were able to help our client innovate in their sector.

The solution

We built a custom AI solution to assist with wound hygiene. We wrote algorithms to segment and classify images of wounds, identifying and categorising metrics like the extent and type of wound tissue - e.g. infection, maceration, slough etc.

The tricky part was not only to identify whether these tissue types were present, but also to identify exactly where on the wound they occurred, labelling the boundaries of each tissue type on the image itself. Using pre-labelled training data for supervised learning, the algorithm could then identify and advise the appropriate course of treatment and dressing. Clever stuff.

Of course, having a human in the loop is still important, so we built in a feedback system for users to either accept or reject recommendations, which over time further improves the accuracy of the system. Correct classifications strengthened the data set; rejected ones were queued for manual review by clinicians.

All this data allowed for much more meaningful reporting on patient outcomes. With complete and standardised records of wounds and wound care, users could now more accurately compare treatments, and predict the time it should take a patient to heal.

With this knowledge, you also become much better able to predict supply and demand of wound care products, and forecast more effectively. All round? It means a tighter grasp of how patient outcomes impact commercial decisions, for both users and suppliers of medical technology.

Our system opens up a whole new set of possibilities for our client, to offer data-driven and AI enabled benefits to their own customers, setting them ahead of the competition.

We know this is how it all starts, and when we say ‘all’, what we mean is the future of healthcare and medical tech. Taking the leap into AI to solve your short-term problem is the first step on the way to innovating in ways you’ve not even thought of yet.

Maybe we should talk about what AI could look like in your business?

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