Exclusive whitepaper

Transforming breast screening at scale: The role of AI in public health systems

Breast cancer screening with mammography has been a cornerstone of public health, credited with reducing mortality through early detection. Yet today’s screening programs face significant challenges: rising imaging volumes, workforce shortages, variability in interpretation, and a one-size-fits-all diagnostic offer. These challenges affect all stakeholders – from public health authorities striving to improve population outcomes, to program managers and center administrators balancing quality and economic efficiency, to radiologists and radiographers tasked with delivering accurate, timely diagnoses under increasing workload.

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What you can expect from this whitepaper:

This in depth document provides a deep dive into the state of mammography screening today, examines how AI solutions address:

Key pain points in radiological settings
real-world results
implementation strategies

The goal is to inform decision-makers – public health officials, screening program managers, radiology department leaders, radiologists, and radiographers – about the tangible advantages AI can bring to their screening programs in both the short and long term.

Transforming Breast Screening in Five Strategic Leaps

Identify and Address Systemic Challenges: Gain a clear picture of today’s screening bottlenecks – from rising imaging volumes and staffing shortages to diagnostic variability and dense breast limitations.
Integrate AI for Clinical and Operational Gains: Discover how AI strengthens every stage of the screening pathway – from real-time image quality control to diagnostic accuracy and automated reporting.
Empower Stakeholders Across the Ecosystem: Learn how radiologists, radiographers, managers, and policymakers each benefit from tailored AI support – enhancing workflows and standardizing care delivery.
Boost Performance with Real-World Results: Understand the impact through landmark studies: up to +20% cancer detection, –44% workload reduction, and –60% inadequate images in just months of AI usage.
Build Scalable, Sustainable Screening Programs: Explore implementation-ready insights for expanding reach and equity – using AI as a lever to meet participation targets and population health goals.