Breast cancer screening reduces mortality, but disparities persist across ethnic and socioeconomic groups. This project aims to address thesse in breast cancer mammography screening outcomes across ethnic and socioeconomic groups in Sweden, particularly with the increasing use of AI systems.
By analyzing approximately 380,000 retrospective screenings linked with demographics from Statistics Sweden, the project will apply AI fairness metrics to assess bias in three commercial and one in-house AI systems, conduct subgroup analyses, and use regression and multilevel modeling for statistical analysis. Stakeholder interviews and focus groups will explore perceptions of bias, and policy recommendations will be developed to enhance fairness and accessibility.
The project will be conducted over three years by a multidisciplinary team from Karolinska Institutet, Lund University, and the Institute for Future Studies. Year 1 will focus on data extraction and initial assessment, Year 2 on AI evaluation and stakeholder engagement, and Year 3 on refining AI systems, pilot testing, and disseminating results. Findings will be disseminated through scientific publications, policy briefs, and training programs, guiding healthcare professionals, policymakers, and AI developers.
The outcomes aim to improve screening accuracy, inform policy, and contribute to broader health equity discussions, ensuring AI supports equitable healthcare and reduces disparities.
IFFS is a project partner in this project which is based at Karolinska institutet, where you will also find the project manager Fredrik Strand.
