Research
Mammographic Breast Density Assessment Using Deep Learning: Clinical Implementation
Purpose: To develop a deep learning (DL) algorithm to assess mammographic breast density.
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“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.
Purpose: To develop a deep learning (DL) algorithm to assess mammographic breast density.
Published 27 January 2021, Sci. Transl. Med
Recent deep learning (DL) approaches have shown promise in improving sensitivity but have not addressed limitations in radiologist specificity or efficiency.