Using machine learning to improve treatment for atrial fibrillation
Machine Learning in Atrial Fibrillation
['FUNDING_R01'] · STANFORD UNIVERSITY · NIH-10814812
This study is exploring how advanced computer technology can help us learn more about atrial fibrillation, a common heart rhythm issue, so we can create better, personalized treatments for patients like you.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | STANFORD UNIVERSITY (nih funded) |
| Locations | 1 site (STANFORD, UNITED STATES) |
| Trial ID | NIH-10814812 on ClinicalTrials.gov |
What this research studies
This research investigates how machine learning can be utilized to better understand and treat atrial fibrillation (AF), a common heart rhythm disorder. By analyzing complex datasets from various levels, including tissue and patient data, the project aims to identify patterns that can help tailor therapies to individual patients. The approach focuses on improving the interpretation of electrograms, understanding the effects of ablation strategies, and predicting patient responses to treatments. This could lead to more personalized and effective management of AF.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals diagnosed with atrial fibrillation who may benefit from tailored therapeutic approaches.
Not a fit: Patients with heart rhythm disorders other than atrial fibrillation may not receive benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized treatments for patients with atrial fibrillation.
How similar studies have performed: Other research has shown promise in using machine learning for similar applications in cardiology, indicating potential for success in this novel approach.
Where this research is happening
STANFORD, UNITED STATES
- STANFORD UNIVERSITY — STANFORD, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: NARAYAN, SANJIV M — STANFORD UNIVERSITY
- Study coordinator: NARAYAN, SANJIV 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.