<?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/E8A688C0-E0B1-4B52-9AA0-5D69452BDAFF" ns1:id="E8A688C0-E0B1-4B52-9AA0-5D69452BDAFF"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/8F504921-1D2D-4481-89CB-4A70622ECE3A" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/3194A536-2E08-4DE7-A8F9-1D6CAF8FFA6F" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/3194A536-2E08-4DE7-A8F9-1D6CAF8FFA6F" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/87E66FA8-E664-4076-9773-15536DB066DF" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2022-03-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/7CB8FF2A-5D34-4541-BCC1-61FE20169997" ns1:rel="FUND" ns1:start="2019-03-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">26673</ns2:identifier></ns2:identifiers><ns2:title>CADDIE - Computer Aided Detection and Diagnosis for Intelligent Endoscopy</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>ISCF</ns2:leadFunder><ns2:abstractText>Colorectal cancer (CRC) is a worldwide disease with 1.3m new cases and 0.7m related deaths reported each year and estimated global economic impact approaching &amp;pound;100 Billion per year. In the UK, CRC is the second most common cause of cancer related deaths, 41k new incidents and over 16k related deaths are reported each year. 230k people are living in the UK with CRC.

Colonoscopy is an important tool for the identification and removal of pre-cancerous and cancerous polyps. However, even with direct inspection of the mucosa, it is highly operator dependent and studies show significant miss rate for polyps and cancers. Furthermore, when abnormal lesions are identified in vivo they are often poorly characterised/diagnosed despite the development of advanced imaging modalities.

Computer Aided Detection and Diagnosis for Intelligent Endoscopy (CADDIE) will disrupt gastroenterology by using artificial intelligence to analyse colonoscopy video images in real-time. CADDIE will automatically detect and analyse cancerous and pre-cancerous polyps with the goal of better earlier detection and diagnosis of cancer leading to better patient outcomes.</ns2:abstractText></ns2:project>