Oct. 7, 2025 – Clairity Inc., a leader in AI-based breast cancer risk prediction, will make five scientific presentations featuring its FDA-authorized image-only AI model at the Radiological Society of North America (RSNA) 2025 Annual Meeting, Nov. 30 to Dec. 4 in Chicago. The studies highlight Clairity’s approach to estimating 5-year breast cancer risk from a single screening mammogram and demonstrate the model’s clinical accuracy, calibration, and utility across diverse global populations.
Selected RSNA abstracts include first-author contributions from Dr. Christiane Kuhl (Chair of Radiology, RWTH Aachen University) and Dr. Elizabeth Morris (Chair of Radiology, UC Davis), reflecting collaboration across leading U.S. and European screening programs. Presentations will be delivered by Clairity Founder Dr. Connie Lehman, and international experts in breast imaging, with findings drawn from multi-center studies in the U.S. and Europe.
Key highlights of Clairity’s participation at RSNA 2025 include:
Scientific Presentations Featuring the CLAIRITY BREAST AI Model
“Predicting Future Risk of DCIS and Invasive Breast Cancer Using AI: A Multi-Site Study in U.S. and European Screening Programs” — Nov. 30, 11:45 am CST
Breast Imaging Sunday Afternoon Poster Discussions I - S3A-SPBR
Why it matters: This study is the first to show that Clairity’s AI model can accurately predict not only invasive breast cancer, but also DCIS (a very early form of breast cancer that remains confined to the milk ducts) across both U.S. and European screening populations. It broadens the clinical relevance of image-only risk scores and supports earlier, more precise intervention.
“External Validation of Discrimination and Calibration of an Image-Only AI Model for 5-Year Breast Cancer Risk Prediction Across Geographically Diverse Screening Sites” — Nov. 30, 2:30 pm CST
Breast Imaging (Breast Cancer Risk Prediction) - S5-SSBR02
Why it matters: A critical real-world test of CLAIRITY BREAST in over 120,000 mammograms across 10 U.S. health systems. The model not only predicted future breast cancer accurately (AUC 0.72), but was also precisely calibrated, meaning the percent risk scores aligned closely with actual outcomes, making them truly actionable for clinicians and patients.
"Image-Only AI Model Compared with Breast Density for Identifying Women at 5-Year Increased Risk of Breast Cancer: Multicenter U.S.-European Analysis” — Nov. 30, 2:30pm CST
Breast Imaging (Breast Cancer Risk Prediction) - S5-SSBR02
Why it matters: Breast density has long been used to estimate risk, but this large multicenter study shows Clairity’s AI model offers far greater precision. It identified women at 2–4x higher risk, including those with non-dense breasts who would be missed by traditional methods, opening the door to smarter screening for more women.
“Targeted Risk Stratification in Women Under 50 Using an Image-Only AI Model: Addressing the Rise in Breast Cancer Incidence in Younger Women” — Dec. 2, 12:45 pm CST
Breast Imaging Tuesday Afternoon Poster Discussions II - T5B-SPBR
Why it matters: Breast cancer is rising fastest in women under 50, yet most risk models weren’t designed for them. This study shows Clairity’s model can find high-risk younger women whose cancer risk rivals that of older age groups, creating a powerful opportunity for earlier detection and prevention in an underserved population.
“Unlocking the Full Value of the Mammogram: Using AI-Based Risk Scores to Detect Cancer, Identify Missed Cancers, and Predict Future Risk” — Dec. 2, 3:15 pm CST
Science Session (Opportunistic Screening: Enhancing Diagnostic Impact from Routine Imaging) - T7-STCE2
Why it matters: Mammograms are typically used to detect cancer that’s already present. This research shows Clairity’s AI model can go further, flagging women at elevated risk of current undetected cancer, missed diagnoses, and future cancers. It demonstrates how a single mammogram can be leveraged for real-time triage and long-term prevention.
Related Research/Educational Panels involving Clairity’s Founder, Dr. Connie Lehman
Educational Session
“Real World Application: Where Are We Heading?” — Dec. 1, 1:30-2:30 pm CST
AI in Mammography and Digital Breast Tomosynthesis: Real-World Applications and Impact - M6-CBR04
Dr. Connie Lehman joins Drs. Ritse Mann and Sarah Friedewald for a forward-looking discussion on clinical integration of AI tools in breast imaging.
Related Research
“Do Deep Learning Breast Cancer Risk Scores Change Meaningfully Over Time? A Longitudinal Analysis” — Dec. 1, 3:00 pm CT
Breast Imaging (Breast Density and Breast Cancer Risk) - M7-SSBR03
Co-authored by Dr. Connie Lehman and collaborators at Mass General Brigham and Weill Cornell, this study evaluated how AI image-based risk scores change over time using serial mammograms. The study, supported by the Breast Cancer Research Foundation, evaluated the dynamic nature of Mirai, a risk model developed in collaboration between MIT and Mass General. This research contributes to the broader scientific understanding of how image-only risk scores may support longitudinal monitoring and personalized screening.
“These presentations reflect the depth of our clinical collaborations, and the real-world impact Clairity is making,” said Jeff Luber, CEO of Clairity. “We’re proud to support visionary researchers who are validating how image-only AI can redefine early detection and improved risk assessment in breast cancer care.”
For meeting details and updates, visit www.clairity.com/rsna2025
December 03, 2025 
