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Congress: ECR24
Poster Number: C-10913
Type: EPOS Radiologist (scientific)
Authorblock: J. H. R. Cairns, B. Riley, H. Ismail, B. Al-Qaisieh, M. Siddique, C. Herbert, B. Wheller, F. U-H. Chowdhury, A. Scarsbrook; Leeds/UK
Disclosures:
James Henry Robert Cairns: Nothing to disclose
Beverley Riley: Nothing to disclose
Hanif Ismail: Nothing to disclose
Bashar Al-Qaisieh: Nothing to disclose
Mohua Siddique: Nothing to disclose
Christopher Herbert: Nothing to disclose
Bob Wheller: Nothing to disclose
Fahmid Ul-Haque Chowdhury: Nothing to disclose
Andrew Scarsbrook: Nothing to disclose
Keywords: Artificial Intelligence, Computer applications, Management, CT, Nuclear medicine conventional, Plain radiographic studies, Cost-effectiveness, Health policy and practice, Technology assessment, Quality assurance
Purpose

Radiology offers an attractive opportunity for deployment of artificial intelligence (AI) solutions because much of the workflow is already digitised, and AI could be part of a potential solution to the well-publicised workforce crisis affecting the National Health Service (NHS)1. AI has the potential to revolutionise clinical workflow, reduce risk, and improve diagnostic accuracy in radiology. However, incorporating AI into routine medical care requires significant organisational transformation, encompassing not only technology adoption but also effective navigation of ethical, legal, and privacy issues that are inherent in AI applications. One approach to creating an ecosystem for imaging AI tool development, prioritisation, evaluation, and patient acceptability undertaken by Leeds Teaching Hospitals NHS Trust (LTHT), a large teaching hospital in Yorkshire, UK, is described.

GALLERY