PrevisionDX is grounded in a growing body of peer-reviewed research demonstrating that mammographic signals carry meaningful cardiovascular information. Below are five studies that anchor the scientific foundation of our work.
Established BAC on routine mammography as associated with higher future cardiovascular risk in postmenopausal women, even after adjustment for traditional risk factors. Supports the foundational premise that mammograms contain cardiovascular information beyond breast cancer screening.
View paper →Large multi-institutional study showing that AI-based quantification of BAC from screening mammograms predicts cardiovascular disease and mortality beyond the AHA PREVENT risk score. Validates the core technical premise that automated mammogram analysis can produce scalable, clinically relevant cardiovascular risk information.
View paper →Demonstrated that lower mammographic breast density is independently associated with higher cardiovascular disease risk, and that adding breast density to the Framingham Risk Score improves prediction and reclassification. Supports the use of breast density as a second cardiovascular signal, strengthening the case for a composite model over a BAC-only approach.
View paper →Showed that an automated BAC score is associated with cardiovascular outcomes and mortality, and that quantifying BAC severity adds more information than simply reporting presence or absence. Supports automated BAC quantification as clinically meaningful and reinforces a quantitative risk scoring approach over manual or binary reporting.
View paper →Demonstrated that BAC can be identified and scored consistently on routine mammograms using structured visual scoring systems, while also showing the variability and limits of visual scoring. Supports the case for automated, quantitative, multi-feature approaches like the CCRI over manual visual scoring alone.
View paper →BAC alone is a powerful signal. Breast density is a complementary one. Combined with AI-derived imaging features and structured clinical context, they form the basis of a longitudinal, explainable cardiovascular risk index designed for women's heart health.