Google Research· Research

Improving breast cancer screening workflows with machine learning

Lihong Xi, Senior Technical Program Manager, and Daniel Golden, Engineering Manager, Google Research A large-scale evaluation of our mammography system across multiple screening services demonstrates its potential to enhance cancer detection accuracy and reduce workload within complex double-reading workflows. Quick links First study Second study Share Copy link × Breast cancer is the leading cause of death for women aged 35–64 in the UK, but research has conclusively shown that early screening through mammography saves lives . The UK's National Health Service (NHS) Breast Screening Programme currently relies on a double-read workflow — two human mammography readers assess each case, and an arbitration panel reviews the case as needed based on local protocols and the results of the two initial reads. While this rigorous process is highly effective, a 30% shortfall of clinical radiologists — projected to reach 40% by 2028 — threatens the long-term sustainability of the program. There has been increasing interest in research efforts …

Announced

17 Mar 2026 16:57 UTC