Core Insights - The largest real-world analysis of AI-driven breast cancer screening in the U.S. shows increased cancer detection rates and equitable benefits across diverse patient populations [1][3] Study Overview - The ASSURE study evaluated the AI-powered workflow in RadNet's Enhanced Breast Cancer Detection™ (EBCD™) program, analyzing mammograms from over 579,000 women across 109 imaging sites in multiple states [2] - The study compared traditional 3D mammography screening with an AI-driven protocol that integrates DeepHealth's FDA-cleared software and a Safeguard Review workflow [2] Results and Findings - The AI-powered workflow resulted in a 21.6% increase in cancer detection rates compared to standard 3D mammography, while maintaining recall rates within guidelines and improving positive predictive value by 15% [3] - For women with dense breasts, the AI workflow achieved a 22.7% increase in cancer detection rates, addressing both higher cancer risk and diagnostic challenges [3] - The study included over 150,000 Black women, highlighting the technology's potential to improve access to care for populations facing higher breast cancer mortality [3] Implementation and Impact - EBCD™ was launched nationwide in 2023, utilizing AI applications from DeepHealth's Breast Suite to enhance detection of difficult-to-find lesions [3] - The study's real-world findings emphasize the ability of AI to improve access to specialist-level care for women, regardless of their location [3] Company Background - RadNet, Inc. is the largest provider of outpatient diagnostic imaging services in the U.S., operating 407 imaging centers across several states [4] - DeepHealth, a subsidiary of RadNet, focuses on AI-powered health informatics to enhance clinical outcomes and operational efficiency in various health domains [5][6]