Developing a new method to predict heart disease risk in breast cancer survivors
Official title: SCH: A New Computational Framework for Learning from Imbalanced Biomedical Data
Funded at University of Minnesota · NIH-10895490 · Data updated 2026-11-12
This study is looking to help breast cancer survivors better understand their heart health by using advanced technology to analyze their medical records, so they can get personalized advice on how to reduce their risk of heart disease.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Minnesota NIH-funded |
| Lab location | 1 site (Minneapolis, United States) |
| Project start | August 1, 2023 |
| Project end | July 31, 2027 |
| Funding year | 2024 |
| Award (this year) | $300,000 |
| NIH project number | 5R01CA287413-02 |
| Project ID | NIH-10895490 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals who have survived breast cancer and are at risk for cardiovascular disease.
✕Less likely to help
Patients who have not been diagnosed with breast cancer or do not have concerns about cardiovascular health may not benefit from this research.
What this research studies
This research focuses on improving the prediction of cardiovascular disease (CVD) risk in breast cancer survivors by utilizing advanced computational techniques. It aims to analyze diverse data from electronic health records (EHR), including clinical notes and imaging data, to create a more accurate risk assessment model. By addressing the imbalanced nature of existing data, the study seeks to provide personalized guidance for managing heart health in individuals who have survived breast cancer. Patients may benefit from tailored prevention strategies based on their unique health profiles.
Why it matters
Potential benefit: If successful, this research could lead to more effective prevention and management strategies for cardiovascular disease in breast cancer survivors.
How similar studies have gone: Previous research has shown promise in using electronic health records for improving disease prediction models, indicating potential success for this novel approach.
Where this research is happening
-
University of Minnesota
Minneapolis, United States Active
Researchers
- Principal investigator: Sun, Ju — University of Minnesota
- Study coordinator: Sun, Ju
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.