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The AI tool analyzes subtle imaging features on screening mammograms that correlate with future risk of breast cancer.
June 5, 2025
By: Sam Brusco
Clairity has received U.S. Food and Drug Administration (FDA) de novo authorization for Clairity Breast, an image-based prognostic platform that leverages artificial intelligence (AI) to predict five-year breast cancer risk from a routine screening mammogram.
The tool analyzes subtle imaging features on screening mammograms that correlate with future risk of breast cancer. The result is a validated five-year risk score that’s delivered through existing clinical infrastructures to support personalized follow-up care.
Clairity built the platform in response to risk assessment models that rely heavily on age and family history to predict breast cancer risk. 85% of women diagnosed with breast cancer don’t have family history of the disease, and almost half don’t have identifiable risk factors.
Further, traditional risk factors are built from predominantly European Caucasian woman and haven’t generalized well to women with diverse racial and ethnic backgrounds.
“For more than 60 years, mammograms have saved lives by detecting early-stage cancers. Now, advancements in AI and computer vision can uncover hidden clues in the mammograms—invisible to the human eye—to help predict future risk,” said Dr. Connie Lehman, founder of Clairity, who is also a breast imaging specialist at Mass General Brigham. “By delivering validated, equitable risk assessments, we can help expand access to life-saving early detection and prevention for women everywhere.”
“Personalized, risk-based screening is critical to improving breast cancer outcomes, and AI tools offer us the best opportunity to fulfill that potential,” added Dr. Robert A. Smith, Senior Vice President of Early Cancer Detection Science at the American Cancer Society. “By integrating AI models that assess individual risk, we can better identify women at higher risk, and those who may benefit from supplemental screening methods, such as MRI, improving early detection and more effective prevention strategies.”
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