Huvudbild för Vitalis 2024
Profilbild för People, Pathways and Performance

People, Pathways and Performance Har passerat

Onsdag 15 maj 2024 14:00 - 14:30 F2

Föreläsare: David Lowe

Spår: Framväxande teknologier

Early diagnosis for lung cancer is  critical to improving patient outcomes as it remains a leading cause of death across the world. Adoption of AI to support enhanced pathways for detection and treatment with the chest radiograph often the initial test performed. This case study describes a framework for evaluating this technology to develop evidence of the solutions potential for cost and clinical effectiveness while assessing technical performance and acceptability. 

Språk

English

Ämne

Kliniska stöd och vårdmodeller

Seminarietyp

Enbart på plats

Föreläsningsformat

Presentation

Föreläsningssyfte

Verktyg för implementering

Kunskapsnivå

Fördjupning

Målgrupp

Chef/Beslutsfattare
Politiker
Upphandlare/inköp/ekonomi/HR
Forskare (även studerande)
Studerande
Omsorgspersonal
Vårdpersonal

Nyckelord

Exempel från verkligheten (goda/dåliga)
Test/validering
Patientsäkerhet

Konferens

Vitalis

Föreläsare

David Lowe Föreläsare

Clinical Director Health Innovation
University of Glasgow

Professor David J Lowe is Clinical Director Innovation University of Glasgow, Emergency Consultant at Queen Elizabeth University Hospital, Glasgow and Clinical Director for Health Innovation for Scottish Government.

David has significant experience of creating the infrastructure and conditions to develop innovative devices, services and solutions with a range of industry and academic partners both UK and worldwide. He is lead for a range of projects across the continuum of digital health including ensemble based AI techniques or osteoporosis as well as supporting evaluation and development of AI solutions across a range of imaging modalities.

He leads on range of projects including trauma for the STN (thetraumaapp.com), Dynamic COPD (support.nhscopd.scot) and OPERA (early diagnostic heart failure utilising AI). Such projects focus on developing AI/ML clinical decision support by embedding a data driven approach combined with patient co-management into clinical care pathways. David also established the EmQuire research group focusing on data, device and decisions within Emergency Medicine.