Collaborative modeling to improve breast cancer outcomes with AI support
Official title: Collaborative Modeling to Identify Strategies to Improve US Breast Cancer Outcomes in an Era of Innovation
Funded at University of Wisconsin-Madison · NIH-11494237 · Data updated 2026-11-12
A national project uses computer models and AI tools to improve how we prevent, screen, and treat breast cancer for people at high risk or after diagnosis.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Wisconsin-Madison NIH-funded |
| Lab location | 1 site (Madison, United States) |
| Project start | September 17, 2026 |
| Project end | August 31, 2031 |
| Funding year | 2026 |
| Award (this year) | $1,839,480 |
| NIH project number | 1U01CA319080-01 |
| Project ID | NIH-11494237 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates include individuals at high inherited risk or elevated risk of breast cancer, patients considering screening or treatment options, and breast cancer survivors.
✕Less likely to help
Patients not involved in screening, prevention, or treatment decision pathways or those outside the defined high-risk groups may see limited direct benefit.
What this research studies
This grant supports a collaborative effort at UW–Madison to translate cutting-edge AI and modeling into real-world breast cancer care. Researchers will combine existing models and new AI insights to forecast outcomes from different risk-reduction, screening, and treatment options and to guide clinical practice. The work focuses on two high-risk groups, long-term population impact of AI in screening, and how post-diagnosis exercise and therapies affect survival and quality of life. Results are intended to help clinicians and patients make better-informed decisions at multiple steps of the care pathway.
Why it matters
Potential benefit: If successful, the project could refine screening and treatment decisions, reducing breast cancer mortality and improving survivor well-being.
How similar studies have gone: The grant builds on CISNET’s established modeling framework with a track record of informing public health decisions; AI-enhanced analyses are an expanding area with promising early results.
Where this research is happening
-
University of Wisconsin-Madison
Madison, United States Active
Researchers
- Principal investigator: Trentham-Dietz, Amy — University of Wisconsin-Madison
- Study coordinator: Trentham-Dietz, Amy
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.