Evaluating AI technologies for breast cancer screening
Population-Based Evaluation of Artificial Intelligence for Mammography Prior to Widespread Clinical Translation
This study is looking at how well different artificial intelligence tools can read mammograms to help find breast cancer in women getting routine screenings, with the hope of making these technologies safe and effective for everyday use.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Washington NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project ID | NIH-10889067 on NIH RePORTER |
What this research studies
This research investigates the effectiveness of various artificial intelligence (AI) technologies in interpreting mammograms to improve breast cancer detection. It aims to assess how these AI systems perform in real-world settings, focusing on their ability to identify clinically significant cancers among women undergoing routine screening. By comparing multiple AI algorithms, the study seeks to provide a comprehensive evaluation that addresses previous limitations in research, such as reliance on single institution data and outdated imaging techniques. The goal is to ensure that these technologies can be safely and effectively integrated into clinical practice for better patient outcomes.
Who could benefit from this research
Good fit: Ideal candidates for this research are women aged 40 and older who are undergoing routine breast cancer screening.
Not a fit: Patients who are not undergoing routine mammography or those with a history of breast cancer may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to improved breast cancer detection rates and better outcomes for women undergoing mammography.
How similar studies have performed: Previous research has shown promise in using AI for mammography, but this study aims to provide a more comprehensive evaluation in a broader population context.
Where this research is happening
Seattle, United States
- University of Washington — Seattle, United States (Active)
Researchers
- Principal investigator: Lee, Christoph I — University of Washington
- Study coordinator: Lee, Christoph I
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 below.