Is Artificial Intelligence the Future of Wound Care?

Background: Machine Learning (ML), a subset of Artificial Intelligence (AI), describes software that can use historical data to inform future decisions. As we continue to move forward into the information age, technological advancements allow us to collect, store and analyze more ‘Big Data’ than ever before. Data Science techniques have shown the ability to leverage medical datasets to derive novel clinical insights (Coudray et al., 2018), guide treatments (Dorman et al., 2016) and predict outcomes (Abràmoff et al., 2016). But what implications does having access to an unprecedented amount of data mean with respect to clinical practices and patient outcomes in wound care?

Methods: Here, the authors have applied data science techniques to wound care datasets. Not only do they provide a current practice picture but also provide a window of opportunity to change the way in which care is delivered. The authors have demonstrated the ability to leverage sophisticated AI/ML techniques to improve wound care workflow, such as automatically identifying tissue types, calculating wound depth, as well as develop novel clinical insights, such as flagging high risk wounds. These types of approaches has been successfully applied in other clinical settings to streamline clinical processes’ and improve patient outcomes. The authors believe that these techniques can be similarly applied to effect positive change in the wound care field.

Conclusions: AI/ML technologies have great potential to improve the delivery of wound care by augmenting clinical workflows and guiding treatments that will improve patient prognosis. AI will not replace clinicians but will leave those that don’t embrace it at a significant disadvantage. Technology impacts our everyday life, much of which is driven by AI/ML, we should accept its impact willingly and help to positively apply to human health.