A Randomised Controlled Trial to Assess if the Implementation of an Artificial Intelligence Mammogram Reader Improves Breast Cancer Screening

  • Frazer, Helen (Primary Chief Investigator (PCI))
  • Carneiro, Gustavo Fluminense (Chief Investigator (CI))
  • Oakden-Rayner, Lauren (Chief Investigator (CI))
  • Reintals, Michelle (Chief Investigator (CI))
  • McCarthy, Davis (Chief Investigator (CI))
  • Lippey, Jocelyn (Chief Investigator (CI))
  • Brotchie, Peter (Chief Investigator (CI))
  • Hopper, John Llewelyn (Chief Investigator (CI))
  • Hepworth, Graham (Chief Investigator (CI))
  • Petrie, Dennis (Chief Investigator (CI))
  • Howard, Mark (Chief Investigator (CI))
  • Sparrow, Robert (Chief Investigator (CI))
  • Kunicki, Katrina (Associate Investigator (AI))
  • Hetzel, Philippa (Associate Investigator (AI))
  • Goldsmith, Suzy (Associate Investigator (AI))
  • Xu, Edward (Associate Investigator (AI))
  • Hocking, Jane Simone (Associate Investigator (AI))
  • Kerrins, Ellen (Associate Investigator (AI))

Project: Research

Project Details

Project Description

The aim of the project is to assess if the inclusion of an artificial intelligence (AI) mammogram reader can improve breast cancer screening accuracy, client and clinician experience, and costs. Whilst AI algorithms demonstrate opportunities to improve breast cancer screening performance in retrospective cohort studies1,2, there has never been a published randomised controlled trial (RCT) evaluating AI readers implemented in real world breast cancer screening populations and clinical settings.
StatusActive
Effective start/end date1/07/23 → 1/07/27

Keywords

  • artificial neural networks
  • breast cancer
  • mammogram screening,
  • population screening
  • randomised controlled trial (RCT)