Using computer models to predict and treat heart rhythm problems
Official title: A population-based computational approach for arrhythmia prediction and therapy
Funded at University of California Los Angeles · NIH-10943723 · Data updated 2026-11-12
This study is looking at new ways to predict and manage irregular heartbeats, called arrhythmias, to help keep people safe and improve treatments, especially since these heart issues can affect everyone differently.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Los Angeles NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project start | July 9, 2024 |
| Project end | June 30, 2028 |
| Funding year | 2024 |
| Award (this year) | $393,750 |
| NIH project number | 1R01HL175074-01 |
| Project ID | NIH-10943723 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals diagnosed with arrhythmias or those at high risk for sudden cardiac death.
✕Less likely to help
Patients with arrhythmias that are not responsive to drug therapies or those who do not have access to the required computational assessments may not benefit from this research.
What this research studies
This research focuses on developing a computational approach to predict and manage arrhythmias, which are irregular heartbeats that can lead to sudden cardiac death. By analyzing data at both individual and population levels, the project aims to improve risk stratification and identify effective drug targets for therapy. The methodology involves understanding the complex interactions that cause arrhythmias, which can vary significantly from person to person. This approach seeks to enhance the efficacy of existing treatments and reduce the risks associated with current antiarrhythmic drugs.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized treatments for patients with arrhythmias, potentially reducing the risk of sudden cardiac death.
How similar studies have gone: Previous research has shown promise in using computational models for predicting arrhythmias, indicating that this approach could lead to significant advancements in treatment.
Where this research is happening
-
University of California Los Angeles
Los Angeles, United States Active
Researchers
- Principal investigator: Qu, Zhilin — University of California Los Angeles
- Study coordinator: Qu, Zhilin
Related research
Other NIH-funded projects on the same topics.
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Understanding how heart nerves affect dangerous heart rhythms after a heart attack
This NIH grant studies how changes in the heart’s nerve signaling after a heart attack lead to dangerous rhythm problems, with the goal of finding ways to prevent them.
-
Dexterous needle ablation for ventricular arrhythmia guided by MRI
A new MRI-guided, robot-assisted catheter delivers deeper heart tissue ablation to treat ventricular tachycardia.
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Sex-specific heart cell signaling and rhythm problems linked to a heart failure drug target
A study from UCLA aims to understand how a key heart signaling pathway controls heart beating and rhythm differently in men and women with heart failure.
-
Additive-made wearable magnetic sensors for heart monitoring with AI
A wearable system using affordable, 3D-printed sensors and machine learning to help detect heart rhythm problems in people.
-
Understanding fat deposits after heart attack and their link to dangerous heart rhythms
A Penn Medicine team is studying how fat buildup in the heart after a heart attack may influence dangerous heart rhythms and recovery.
-
Developing 3D Real-Time CMR for Arrhythmia Imaging
Aims to make real-time 3D heart MRI usable for people with irregular heartbeats to improve how doctors see arrhythmias.
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.