Using AI and genetics to improve breast cancer screening and prevention
Project 3: Integration of mammographic AI, clinical, and genomics information to improve breast cancer subtype-specific risk-based screening and prevention
This study is looking to improve breast cancer screening by using smart technology and genetic information to help identify people who might be at higher risk for certain types of breast cancer, so that you can get a more personalized and effective screening plan just for you.
Quick facts
| Grant type | P01 program project |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project ID | NIH-11177237 on NIH RePORTER |
What this research studies
This research aims to enhance breast cancer screening by integrating advanced artificial intelligence techniques with clinical and genetic information. The project focuses on developing a predictive model that can better identify individuals at risk for specific subtypes of breast cancer, moving beyond traditional screening methods. By leveraging deep-learning AI to analyze mammographic features and incorporating genetic data, the goal is to create a more personalized and effective screening approach. Patients participating in this research may benefit from tailored screening strategies that are more aligned with their individual risk profiles.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals at varying risk levels for breast cancer, particularly those with a family history or genetic predispositions.
Not a fit: Patients who have already been diagnosed with advanced breast cancer may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and personalized breast cancer screening, potentially reducing the incidence of advanced cancers.
How similar studies have performed: Previous studies have shown promise in using AI and genetic information for cancer risk assessment, indicating a strong potential for success in this novel approach.
Where this research is happening
San Francisco, United States
- University of California, San Francisco — San Francisco, United States (Active)
Researchers
- Principal investigator: Arasu, Vignesh a — University of California, San Francisco
- Study coordinator: Arasu, Vignesh a
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.