Using machine learning to predict heart disease risk in patients with a specific blood condition
Personalized Prediction of Cardiovascular Outcomes through Machine Learning Analysis of Cardiac MRI and Genomics
This study is looking at how computer technology can help doctors predict heart problems in people with a condition called Clonal Hematopoiesis of Indeterminate Potential (CHIP) by analyzing heart scans and genetic information, so they can provide better, personalized care even before any symptoms appear.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project ID | NIH-11175780 on NIH RePORTER |
What this research studies
This research investigates how machine learning can analyze cardiac MRI and genomic data to predict cardiovascular outcomes in patients with Clonal Hematopoiesis of Indeterminate Potential (CHIP). By utilizing advanced algorithms, the study aims to identify patients at risk of heart failure or myocardial infarction, even if they do not currently show symptoms. The approach involves evaluating heart images and genetic information to create risk scores that help in understanding individual patient risks. This could lead to more personalized treatment plans and better management of heart health.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals diagnosed with Clonal Hematopoiesis of Indeterminate Potential (CHIP), including both cancer and non-cancer patients.
Not a fit: Patients without CHIP or those who do not have cardiovascular risk factors may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could enable earlier identification and intervention for patients at risk of heart disease, potentially improving their health outcomes.
How similar studies have performed: Previous research has shown promise in using machine learning techniques for predicting cardiovascular outcomes, suggesting that this approach could be effective.
Where this research is happening
New Haven, United States
- Yale University — New Haven, United States (Active)
Researchers
- Principal investigator: Kwan, Jennifer M — Yale University
- Study coordinator: Kwan, Jennifer M
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.