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Updated: Jul 15, 2025

Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis
Published on: February 6, 2020
Cost-effectiveness requirements for implementing artificial intelligence technology in the Women's UK Breast Cancer
Armando Vargas-Palacios1,2, Nisha Sharma3, Gurdeep S Sagoo4,5
1Academic Unit of Health Economics, University of Leeds, Leeds, UK. a.vargas-palacios@leeds.ac.uk.
Abstract:
The UK NHS Women's National Breast Screening programme aims to detect breast cancer early. The reference standard approach requires mammograms to be independently double-read by qualified radiology staff. If two readers disagree, arbitration by an independent reader is undertaken. Whilst this process maximises accuracy and minimises recall rates, the procedure is labour-intensive, adding pressure to a system currently facing a workforce crisis. Artificial intelligence technology offers an alternative to human readers. While artificial intelligence has been shown to be non-inferior versus human second readers, the minimum requirements needed (effectiveness, set-up costs, maintenance, etc) for such technology to be cost-effective in the NHS have not been evaluated. We developed a simulation model replicating NHS screening services to evaluate the potential value of the technology. Our results indicate that if non-inferiority is maintained, the use of artificial intelligence technology as a second reader is a viable and potentially cost-effective use of NHS resources.

