<?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/9B73FF31-6AA1-494A-9059-060AF985D2E9" ns1:id="9B73FF31-6AA1-494A-9059-060AF985D2E9"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/5C8FE594-41E3-46BF-948D-0FB9C6DBD42D" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/1ED88DE0-5306-467C-9836-F5552D66D5C4" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/1ED88DE0-5306-467C-9836-F5552D66D5C4" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2021-04-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/39BB2B44-829E-406E-A310-7202424D1C7C" ns1:rel="FUND" ns1:start="2020-07-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">72665</ns2:identifier></ns2:identifiers><ns2:title>0238 AI Classification of COVID - 19 studies to ensure clinical guidance and healthcare policy is informed by current meta-analysis of all available evidence</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>This project will deliver a new set of machine learning (AI) models to classify COVID-19 human-based clinical studies with structured data from Cochrane's bioinformatics vocabularies.

This innovation will enable the discovery, evaluation and synthesis of the most relevant and up-to-date COVID-19 primary evidence from around the world, to answer as quickly and comprehensively as possible specific clinical questions currently being prioritised by clinicians and healthcare policy advisers.</ns2:abstractText></ns2:project>