<?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="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/AB44E8DF-B5D1-41FF-AB4E-852B864F3D3B" ns1:id="AB44E8DF-B5D1-41FF-AB4E-852B864F3D3B"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/C5626076-F2F5-4A78-9B2C-B6AB1CB54030" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/E3A8EE60-A97A-424A-A466-1E0C5A14DBB9" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/E3A8EE60-A97A-424A-A466-1E0C5A14DBB9" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2023-11-30T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/6444F933-51DE-4761-A7D4-CE230480021F" ns1:rel="FUND" ns1:start="2023-05-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10076466</ns2:identifier></ns2:identifiers><ns2:title>AI Trust Audit - A novel solution and process to advance trust in the compliance and risk of AI systems in radiology</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Grant for R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Radiology AI products have the potential to revolutionise the healthcare industry by improving patient outcomes, reducing errors, and increasing efficiency. However, the adoption of these products has been slow due to concerns over their reliability, robustness, and compliance. The lack of transparency in the development and testing of AI systems has raised questions about their safety and effectiveness.

The AI Trust Audit project aims to develop a novel solution to advance trust in the compliance and risk of AI systems auditing, impact assessment, or evaluation, reliability and robustness testing of radiology AI products. This project is essential as radiology AI products are becoming more widely used, and there is a growing need to ensure that they are reliable, trustworthy and have a positive impact on patients and healthcare providers.

The proposed solution will be a software-based AI Trust Audit tool, which will use machine learning algorithms to assess the compliance, risk, and reliability of radiology AI products. The tool will perform automated testing and auditing, as well as impact and risk assessments, to identify potential issues with reliability of these products. The tool will be designed to integrate seamlessly with existing radiology workflows and software systems, making it easy for healthcare providers to use and adopt.

The impact of this project will be significant for patients, healthcare providers, and the wider healthcare industry. The AI Trust Audit tool will improve patient safety by identifying and addressing potential issues with radiology AI products before they cause harm. It will also provide healthcare providers with greater confidence in the reliability and performance of these products, leading to increased adoption and improved patient outcomes.

In addition to the positive impact on patient outcomes, this project will also benefit the UK economy by supporting the development of a new and innovative healthcare technology. Overall, the AI Trust Audit project is a crucial step forward in ensuring the safe and effective use of radiology AI products. By developing a comprehensive and automated tool that addresses the unique challenges and risks of these products, this project has the potential to revolutionise the way radiology AI products are tested, evaluated, and audited.</ns2:abstractText></ns2:project>