Improving breast cancer screening for diverse populations.
Official title: ADVANCING EQUITY AND DIVERSITY IN BREAST CANCER SCREENING: CREATING A FOUNDATIONAL DATASET AND TOOLSET.
Funded at Gradient Health INC · NIH-11215669 · Data updated 2026-11-12
This study is working to improve breast cancer screening for everyone by gathering important health information from different racial and ethnic groups, so that the technology used to detect breast cancer can be better and fairer for all women.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Gradient Health INC NIH-funded |
| Lab location | 1 site (Durham, United States) |
| Project start | September 16, 2024 |
| Project end | September 15, 2025 |
| Funding year | 2024 |
| Award (this year) | $388,108 |
| NIH project number | 75N91024C00061-0-9999-1 |
| Project ID | NIH-11215669 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals from various racial and ethnic backgrounds who are undergoing or have undergone breast cancer screening.
✕Less likely to help
Patients who do not have access to breast cancer screening or those who are not part of the targeted racial and ethnic groups may not benefit from this research.
What this research studies
This research aims to address disparities in breast cancer screening by creating a comprehensive dataset that includes important physiological characteristics, such as breast density and tumor markers, across different racial and ethnic groups. By collecting and linking data from mammograms, pathology reports, and genetic information, the project seeks to enhance the training of AI algorithms used in breast cancer detection. This will help ensure that these algorithms are more effective and equitable for all populations, ultimately improving screening outcomes.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and equitable breast cancer screening for diverse populations, potentially saving lives.
How similar studies have gone: Other research has shown success in improving medical algorithms by incorporating diverse datasets, suggesting that this approach could be effective.
Where this research is happening
-
Gradient Health INC
Durham, United States Active
Researchers
- Principal investigator: Huang, Ouwen — Gradient Health INC
- Study coordinator: Huang, Ouwen
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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.