Improving stroke risk prediction for patients with atrial fibrillation.
Official title: Personalized Stroke Risk Stratification in Atrial Fibrillation: Integrating Probabilistic Graphical Models and High-dimensional EHR Data for Interpretable Prognosis
Funded at Denver Health and Hospital Authority · NIH-11025957 · Data updated 2026-11-12
This study is working on a new tool to help predict stroke risk for people with atrial fibrillation by looking at both health and social factors, so that doctors can better tailor prevention strategies just for you.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Denver Health and Hospital Authority NIH-funded |
| Lab location | 1 site (Denver, United States) |
| Project start | April 7, 2025 |
| Project end | March 31, 2030 |
| Funding year | 2025 |
| Award (this year) | $540,771 |
| NIH project number | 1R01HL177105-01 |
| Project ID | NIH-11025957 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with atrial fibrillation who may be at risk for stroke.
✕Less likely to help
Patients without atrial fibrillation or those who do not have risk factors for stroke may not benefit from this research.
What this research studies
This research aims to create a personalized tool for predicting stroke risk in patients with atrial fibrillation (AF) by integrating advanced data analysis techniques. It will explore new risk factors, including social determinants of health, and combine them with existing factors using machine learning to enhance understanding and explainability. The goal is to develop a tool that can be used across different healthcare systems to improve stroke prevention strategies tailored to individual patient needs.
Why it matters
Potential benefit: If successful, this research could lead to more accurate stroke risk assessments and better prevention strategies for patients with atrial fibrillation.
How similar studies have gone: Previous research has shown promise in using machine learning and social determinants of health to improve risk stratification in various medical conditions, indicating potential success for this approach.
Where this research is happening
-
Denver Health and Hospital Authority
Denver, United States Active
Researchers
- Principal investigator: Steinberg, Benjamin Adam — Denver Health and Hospital Authority
- Study coordinator: Steinberg, Benjamin Adam
Related research
Other NIH-funded projects on the same topics.
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Personalized stroke risk prediction for atrial fibrillation patients using advanced data and models
Aims to create a personalized, easy-to-use tool that predicts stroke risk for people with atrial fibrillation using big health data and transparent machine-learning methods.
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This NIH grant explores how a heart protein called JNK2 may drive atrial fibrillation, blood clots, and stroke, and whether it could serve as a biomarker and new treatment approach.
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DECIDE-AF: a shared decision tool in your health portal to help prevent strokes in atrial fibrillation
A patient-friendly tool in your electronic health record helps you and your doctor choose the right way to prevent strokes if you have atrial fibrillation.
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Aims to combine data from three big trials to understand how decision aids help people with atrial fibrillation choose anticoagulation to prevent stroke, in a patient-centered way.
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Precursors of Stroke Incidence and Prognosis
This grant explores how life-long vascular risk factors and stroke-related brain changes influence the risk of cognitive problems, including Alzheimer’s-type dementia, in diverse adults.
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New AI approach to detect and predict atrial fibrillation after stroke
A patient-friendly AI-based method is being developed to spot atrial fibrillation early in people who have had a stroke, using wearable heart-rate signals.
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.