Improving heart surgery planning using advanced simulations and AI
Official title: SCH: Simulation Optimization of Cardiac Surgical Planning
Funded at University of Tennessee Knoxville · NIH-10924039 · Data updated 2026-11-12
This study is looking to improve surgery results for people with atrial fibrillation by using smart technology and simulations to help doctors make better decisions during the procedure, aiming for more personalized care and better outcomes for patients.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Tennessee Knoxville NIH-funded |
| Lab location | 1 site (Knoxville, United States) |
| Project start | September 7, 2023 |
| Project end | August 31, 2027 |
| Funding year | 2024 |
| Award (this year) | $289,466 |
| NIH project number | 5R01HL172292-02 |
| Project ID | NIH-10924039 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients diagnosed with atrial fibrillation who are considering catheter ablation as a treatment option.
✕Less likely to help
Patients with arrhythmias other than atrial fibrillation or those who are not candidates for catheter ablation may not benefit from this research.
What this research studies
This research focuses on enhancing surgical outcomes for patients with atrial fibrillation through the use of advanced simulations and artificial intelligence. By integrating sensor data from patients who have undergone catheter ablation, the project aims to develop optimized planning methodologies that can improve decision-making during surgery. The approach combines physics-based modeling with machine learning to better understand and predict surgical outcomes, ultimately leading to more personalized treatment plans for patients. The research seeks to address the variability in surgical success rates by leveraging modern data processing techniques.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized surgical interventions for patients with atrial fibrillation, improving their overall health outcomes.
How similar studies have gone: Other research has shown promising results using AI and simulation techniques in surgical planning, indicating that this approach has the potential for significant advancements in cardiac care.
Where this research is happening
-
University of Tennessee Knoxville
Knoxville, United States Active
Researchers
- Principal investigator: Yao, Bing — University of Tennessee Knoxville
- Study coordinator: Yao, Bing
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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.