Using computers to predict the best treatment for dangerous ventricular heart rhythms
Machine Learning for Ventricular Arrhythmias
This project uses machine learning and computer heart simulations to find which people with ventricular tachycardia are most likely to benefit from medications or catheter ablation.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project ID | NIH-11098652 on NIH RePORTER |
What this research studies
You would benefit if researchers can use large collections of patient records, lab results, and non-invasive heart imaging to teach computer algorithms about treatment responses. They will also build computer models that simulate whether an individual heart is likely to keep producing dangerous rhythms before and after treatment. Predictions will be checked against large external hospital registries to make sure the methods work across different patient groups. The aim is to combine clinical data and simulations so treatment choices for ventricular tachycardia can be more personalized.
Who could benefit from this research
Good fit: Adults with ventricular tachycardia or ventricular fibrillation who have clinical records, lab tests, and non-invasive cardiac imaging available are the most likely candidates.
Not a fit: People without ventricular arrhythmias, those lacking relevant medical records or imaging, or those needing immediate emergency care would not be candidates for this work.
Why it matters
Potential benefit: Could help doctors match each patient to the treatment—drug or ablation—most likely to work, reducing ineffective care and complications.
How similar studies have performed: Prior machine-learning efforts in this area have shown promise with data analysis but have not yet translated into better patient outcomes, so combining ML with patient-specific heart models is relatively new.
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.