<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/085409D6-FBB8-4B61-B595-05EA97A285B2" ns1:id="085409D6-FBB8-4B61-B595-05EA97A285B2"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/92CFBE66-3A75-4439-899D-99902733EE45" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/9BC19B36-D8B1-4B0F-AE27-D7E379B65B47" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/9BC19B36-D8B1-4B0F-AE27-D7E379B65B47" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-01-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/511FC519-050F-4BD1-9624-419F03BE8819" ns1:rel="FUND" ns1:start="2023-05-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10075117</ns2:identifier></ns2:identifiers><ns2:title>TAIMWAS: A Trustworthy AI Model-based Intelligent Chronic Wound Analysis System</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Grant for R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The project will develop intelligent software/app for mobile/tablet that can work as an end-to-end solution for a fully automated wound analysis system. This software will deploy multiple **robust** and **verifiable** deep learning (DL) models to analyse 2D/3D images and extract information about various aspects of wounds for intelligent and efficient management. The DL models will be trained/updated through a federated learning (FL) approach to improve data diversity, preserve users' privacy, and minimise security risk. We will also use a deep generative model to verify the accuracy of the models trained. Thus, the robustness and verifiability of the models will make our solution **TAIMWAS** trustworthy. And this is the first **trustworthy AI system** that offers end-to-end wound management services using FL using multi-site and diverse image data. In addition, the solution's accurate non-contact measurements, automated facility reporting, and analytics will enhance clinical productivity, reduce clinical variability and quality patient outcomes, and minimise risk &amp;amp; liability.</ns2:abstractText></ns2:project>