Using advanced modeling to improve nerve stimulation treatments for bladder issues
A new hybrid modeling framework combining biophysics and deep learning to predict and optimize peripheral neuromodulation outcomes in lower urinary tract disease
This study is working on a new way to improve treatments for bladder problems by using a mix of science and smart computer technology to find the best nerve stimulation therapies, which could help patients get better care faster without relying too much on animal testing.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Emory University NIH-funded |
| Lab location | 1 site (Atlanta, United States) |
| Project ID | NIH-11066155 on NIH RePORTER |
What this research studies
This research aims to enhance treatments for lower urinary tract dysfunction by developing a new hybrid modeling framework that combines biophysics and deep learning. By creating a predictive model, the researchers hope to simulate various nerve stimulation therapies more efficiently, allowing them to identify the most promising treatment options without the need for extensive animal testing. This approach could significantly speed up the development of targeted neuromodulation therapies, ultimately improving patient outcomes. The project will integrate detailed physiological models with advanced AI techniques to better understand and predict how the bladder responds to different stimulation parameters.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals experiencing lower urinary tract dysfunction who may benefit from neuromodulation therapies.
Not a fit: Patients with urinary tract issues not related to neuromodulation or those who do not respond to nerve stimulation therapies may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized treatments for patients suffering from lower urinary tract dysfunction.
How similar studies have performed: While the integration of biophysics and deep learning in this context is innovative, similar modeling approaches have shown promise in other areas of medical research.
Where this research is happening
Atlanta, United States
- Emory University — Atlanta, United States (Active)
Researchers
- Principal investigator: Danziger, Zachary C — Emory University
- Study coordinator: Danziger, Zachary C
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.