Chronic wounds represent a significant and increasing challenge for healthcare. Recent new insights and advances in wound treatment are not finding their way into clinical practice quickly enough.
Steven Smet's PhD project, based on literature research and qualitative research into the clinical reasoning of nurses and general practitioners, is working on a new algorithm to choose a correct wound treatment based on specific anamnesis and targeted clinical examiniation. This algorithm is currently being validated and will subsequently be tested in clinical practice.
The use of AI tools and extensive databases with wound parameters and AI analyzes can ensure a more uniform and reliable wound evaluation and thus a more predictable therapeutic effect. 
In concrete terms, we want to use the information collected with the AI-SWEEP project to further optimize the wound assessment and integrate this into a further version of the wound care algorithm to achieve more efficient and more cost-effective wound treatment.