<?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/9143C9F0-6EE2-4CDA-93F4-2198B9E779BE" ns1:id="9143C9F0-6EE2-4CDA-93F4-2198B9E779BE"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/D39CEAA3-7F74-426D-9DD0-47EEBC9A0D5A" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/9FBFA687-3B6F-45D9-AD49-F1BF189884A7" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/9FBFA687-3B6F-45D9-AD49-F1BF189884A7" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-03-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/75950C59-3AC7-4BC4-BFF9-0C2B900BC6AF" ns1:rel="FUND" ns1:start="2022-09-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10035750</ns2:identifier></ns2:identifiers><ns2:title>An innovative electronic preoperative assessment solution using GP data and ML/AI models that could reduce nursing time required per patient by 40%</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Aire Logic Limited is a UK digital health SME with a core project team of Michael Odling-Smee, Alwyn Kotzee, Kevin Maguire and Cairen Ball. AireLogic is developing a solution that enables preoperative assessments to incorporate GP records and improve their efficiency. Hospitals currently conduct preoperative assessments manually, relying on patient s' own knowledge of their medical history, costing &amp;pound;99M/year. Improving this process is crucial to addressing NHS England's waiting list, which now stands at 5.98M people. The solution enables a range of interactions between patients and assessors and supports preassessment through automation and data transformation, enabling nurses to spend their time more productively.</ns2:abstractText></ns2:project>