A landmark study published in Nature Health has demonstrated the effectiveness of DeepHealth’s AI-powered breast cancer detection workflow in one of the largest real-world analyses of AI-driven breast cancer screening in U.S. history. The AI-Supported Safeguard Review Evaluation (ASSURE) study evaluated RadNet’s Enhanced Breast Cancer Detection™ (EBCD™) program, which integrates DeepHealth’s FDA-cleared computer-aided detection and diagnosis (CADe/x) software with an AI-supported Safeguard Review workflow that triggers a second expert review for high-suspicion cases. The study analyzed over 579,000 mammograms from 109 community-based imaging centers across California, Delaware, Maryland, and New York. Results showed a 21.6% increase in cancer detection rates compared to standard 3D mammography screening, while maintaining recall rates within guidelines set by the American College of Radiology and improving positive predictive value by 15%. Notably, the AI-powered workflow delivered consistent benefits across diverse patient populations. Among more than 150,000 Black women enrolled—whose breast cancer mortality rates are 40% higher than those of white women—the technology demonstrated equitable improvements in detection. For women with dense breasts, who face both higher cancer risk and greater diagnostic challenges, the detection rate improved by 22.7%. Unlike many academic studies, this research was conducted in real-world community imaging settings where most women receive their screenings. To minimize selection bias, the AI-enhanced workflow was offered to all patients at no additional cost during the study period. Dr. Gregory Sorensen, co-author and Chief Science Officer at RadNet, emphasized that the findings show how AI can extend specialist-level care to underserved communities and improve early detection, which is critical for better treatment outcomes. The EBCD™ program, launched nationwide in 2023, is powered by DeepHealth’s Breast Suite, a suite of AI applications designed to identify subtle and hard-to-detect lesions. The technology operates within DeepHealth OS, a cloud-native platform that unifies clinical and operational data to create personalized, efficient workflows for radiologists. RadNet, Inc., the parent company of DeepHealth, is the largest provider of outpatient diagnostic imaging services in the U.S., operating 407 imaging centers across multiple states. DeepHealth, a wholly owned subsidiary, brings together leading AI solutions in breast, lung, prostate, brain, and thyroid health, with a mission to improve early disease detection and clinical outcomes. The study’s findings underscore the potential of AI to transform breast cancer screening by increasing detection accuracy, reducing disparities, and enhancing access to high-quality care—particularly in community-based settings where resources may be limited.