Improving breast cancer screening using advanced AI technology
Official title: SCH: Robust Multimodal Longitudinal AI for Enhanced Breast Cancer Screening
Funded at University of Connecticut Storrs · NIH-11063443 · Data updated 2026-11-12
This study is working on using smart computer technology to make mammograms better at finding breast cancer, so women can get more accurate results and earlier diagnoses.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Connecticut Storrs NIH-funded |
| Lab location | 1 site (Storrs-Mansfield, United States) |
| Project start | August 1, 2024 |
| Project end | July 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $310,317 |
| NIH project number | 1R01CA297855-01 |
| Project ID | NIH-11063443 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are women aged 40 and older who are undergoing routine breast cancer screening.
✕Less likely to help
Patients who are not undergoing breast cancer screening or those with advanced breast cancer may not benefit from this research.
What this research studies
This research aims to enhance breast cancer screening by developing advanced artificial intelligence algorithms that optimize the detection process. It focuses on improving the accuracy of mammograms, particularly 3D mammography, which is increasingly used for its ability to provide detailed views of breast tissue. By addressing the challenges faced by radiologists, such as high workloads and the risk of false positives, this project seeks to create a more reliable screening method that can lead to earlier and more accurate diagnoses for women. The study will utilize deep learning techniques to analyze mammogram images and improve clinical decision-making.
Why it matters
Potential benefit: If successful, this research could lead to more accurate breast cancer screenings, reducing false positives and missed diagnoses, ultimately improving patient outcomes.
How similar studies have gone: Other research has shown promising results using AI in medical imaging, indicating that this approach has the potential for significant advancements in breast cancer detection.
Where this research is happening
-
University of Connecticut Storrs
Storrs-Mansfield, United States Active
Researchers
- Principal investigator: Nabavi, Sheida — University of Connecticut Storrs
- Study coordinator: Nabavi, Sheida
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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.