“Too many patients are given a cancer diagnosis when it’s too late to help them. It’s time to empower everyone, everywhere, with the information and choices we all deserve.”
Dr. Connie Lehman
Clairity’s rigorous, evidence-based approach to AI solution development is grounded in decades of breakthrough population health and radiomics research conducted by Dr. Connie Lehman at top academic medical centers including MassGeneral Brigham, MIT, and the University of Washington.
Accuracy
Improve early detection and
diagnosis
Equity
Address racial and
ethnic bias
Precision
Tailor the plan of care to each individual
Engagement
Empower patients to make informed decisions
Just like genetics, imaging data captures key insights about risk. It’s time to unlock and share those insights.
Deep learning breast cancer risk models demonstrate improved accuracy compared to traditional risk models. This research highlights the promise deep learning models to support equitable, risk-based mammography screening.
Accurate density assessments could help health care systems more appropriately use limited supplemental screening resources and help better inform traditional clinical risk models.
The COVID-19 pandemic took a toll on mammography screening volumes among women of color, slashing exam uptake by more than 50% between 2019 and 2020.
