An NCCN-recognized AI-driven method to estimate a woman’s likelihood of developing invasive breast cancer within five years.
It reveals patterns invisible to the human eye and translates them into an absolute risk estimate that clinicians can trust.
Our solution is designed to use only the patient’s mammogram and age. No questionnaires, no reliance on clinical history.
Risk assessment becomes more accessible, more consistent, and easier to apply at scale—directly within existing screening workflows.
Outputs will be delivered as 5-year absolute risk, calibrated to SEER incidence data—giving clinicians a clear, interpretable score aligned to real-world population risk.
Trained on real-world U.S. screening cohort data, the model is designed to predict future risk, not detect disease.
Today, risk and detection are understood through different, yet complementary lenses.
Traditional models look to the long term. Detection focuses on what is present now. Image-based risk adds a new layer—unlocking short-term insight directly from the mammogram, at the time of screening.
Together, they create a more connected, continuous view of breast health over time.
Access in-depth resources on how image-based risk fits into clinical practice, alongside expert insights shaping the future of risk assessment.
