Improving prediction of major cardiovascular events using advanced data techniques
Official title: SCH: Transfer Regression to Enable Cross-Domain Cardiovascular Event Prediction
Funded at Case Western Reserve University · NIH-11062600 · Data updated 2026-11-12
This study is working on a new tool that uses smart technology to help doctors predict serious heart problems like strokes and heart attacks, making it easier and safer for patients to get checked and improve their heart health.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Case Western Reserve University NIH-funded |
| Lab location | 1 site (Cleveland, United States) |
| Project start | September 1, 2024 |
| Project end | August 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $299,604 |
| NIH project number | 1R01HL177813-01 |
| Project ID | NIH-11062600 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals at risk for cardiovascular diseases, such as those with high blood pressure or a family history of heart conditions.
✕Less likely to help
Patients who are not at risk for cardiovascular events or those with existing severe cardiovascular conditions may not benefit from this research.
What this research studies
This research aims to develop a new model for predicting major cardiovascular events such as strokes and heart attacks using innovative machine learning techniques. By utilizing low-cost and safe screening methods, the project seeks to create a standardized and user-friendly prediction tool that can be applied in clinical settings. The model will be validated with large datasets to ensure its effectiveness and reliability, ultimately aiming to enhance patient outcomes in cardiovascular health.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of cardiovascular events, allowing for timely and targeted preventive therapies.
How similar studies have gone: Other research has shown promise in using machine learning for health predictions, indicating that this approach could be effective.
Where this research is happening
-
Case Western Reserve University
Cleveland, United States Active
Researchers
- Principal investigator: Li, Shuo — Case Western Reserve University
- Study coordinator: Li, Shuo
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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.