Improving heart resuscitation methods for children using machine learning
Official title: Evaluating and improving the efficacy of Extracorporeal Cardiopulmonary Resuscitation (ECPR) in pediatric patients using interactive Machine Learning
Funded at Villanova University · NIH-11000848 · Data updated 2026-11-12
This study is looking to improve the chances of survival and brain health for kids who have a cardiac arrest by using smart computer technology to find out which children might benefit the most from a special treatment called ECPR.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Villanova University NIH-funded |
| Lab location | 1 site (Villanova, United States) |
| Project start | January 1, 2024 |
| Project end | December 31, 2025 |
| Funding year | 2025 |
| Award (this year) | $111,651 |
| NIH project number | 5R21HL167181-02 |
| Project ID | NIH-11000848 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are hospitalized children under 21 years old who experience cardiac arrest.
✕Less likely to help
Patients who do not experience cardiac arrest or are outside the pediatric age range may not benefit from this research.
What this research studies
This research focuses on enhancing the effectiveness of Extracorporeal Cardiopulmonary Resuscitation (ECPR) for pediatric patients experiencing cardiac arrest. By utilizing advanced machine learning algorithms, the project aims to analyze a large dataset to identify specific patient characteristics that predict who may benefit from ECPR. The goal is to improve survival rates and neurological outcomes for children who suffer from cardiac arrest, a condition that currently has low survival rates. The research will involve collecting and processing data related to patients' demographics, physiological, and biochemical factors.
Why it matters
Potential benefit: If successful, this research could significantly increase the survival rates and quality of life for children who experience cardiac arrest.
How similar studies have gone: Previous research has shown promising results in using machine learning for improving resuscitation techniques, indicating potential for success in this novel approach.
Where this research is happening
-
Villanova University
Villanova, United States Active
Researchers
- Principal investigator: Nataraj, Chandrasekhar — Villanova University
- Study coordinator: Nataraj, Chandrasekhar
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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.