Using artificial intelligence to improve breast cancer screening accuracy.
Artificial Intelligence for Improved Breast Cancer Screening Accuracy: External Validation, Refinement, and Clinical Translation
This study is working on using smart computer technology to make breast cancer screenings more accurate, so that women can catch any issues earlier and have better treatment options.
Quick facts
| Grant type | R37 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Washington NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project ID | NIH-10879693 on NIH RePORTER |
What this research studies
This research focuses on enhancing the accuracy of breast cancer screening through the use of artificial intelligence (AI). It aims to validate and refine a proven AI algorithm for interpreting 2D mammograms and adapt it for 3D mammography. By leveraging large datasets and advanced computing capabilities, the project seeks to reduce the number of missed cancers and false positives that currently affect screening outcomes. Patients may benefit from more accurate screenings, leading to earlier detection and better treatment options.
Who could benefit from this research
Good fit: Ideal candidates for this research are women undergoing routine breast cancer screenings, particularly those who may benefit from 3D mammography.
Not a fit: Patients who have already been diagnosed with breast cancer or those who are not eligible for mammography may not receive benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate breast cancer screenings, reducing missed diagnoses and unnecessary follow-ups.
How similar studies have performed: Previous research has shown promise in using AI for medical imaging, indicating that this approach could lead to significant advancements in breast cancer screening accuracy.
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.