Susan G. Komen has awarded $15.4 million in grants to breast cancer researchers, including those in medical imaging, with funded projects spanning the use of AI for better health outcomes and vaccine-based approaches targeting the most aggressive and deadliest forms of breast cancer.
In total, 35 researchers representing 24 leading medical and research institutions in the U.S. received funding. One funded project will explore how radiation therapy combined with drug treatment or surgery can be personalized using biomarkers to improve patient response. Another study will find out how AI-derived breast cancer imaging risk scores are affected by weight loss drugs.
The investment by Komen includes support for long-term, well-established researchers who have made a profound impact in the field and early-career investigators whose work represents the next generation of scientific discovery and innovation in breast cancer research, according to the organization.
The grants also support research on breast cancer in younger populations, the role of weight loss on breast cancer risk and prevention, and reducing disparities in breast cancer outcomes for all.
Komen said 72% of its funding is dedicated to metastatic breast cancer, while 88% is focused on precision medicine to tailor treatments to each patient’s unique biology.
Click here for the full list of funding recipients and their respective research projects.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
