Using machine learning to improve treatment for patients with shortness of breath
SCH: Leveraging Clinical Time Series to Learn Optimal Treatment of Acute Dyspnea
This study is exploring a new way to help doctors treat patients who are having trouble breathing by using smart technology to find out which treatments work best for them in real-time.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Michigan at Ann Arbor NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project ID | NIH-10458527 on NIH RePORTER |
What this research studies
This research focuses on enhancing the treatment of patients experiencing acute dyspnea, or shortness of breath, by utilizing a novel machine learning approach known as reinforcement learning. Instead of merely diagnosing conditions, this method analyzes clinical time-series data from electronic health records to determine how different treatments affect patient outcomes. By simulating various treatment strategies, the framework aims to provide physicians with real-time insights into the most effective interventions for their patients. This approach is particularly beneficial for patients whose symptoms may arise from multiple overlapping conditions, making treatment decisions complex.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients hospitalized with acute dyspnea and signs of respiratory failure.
Not a fit: Patients with chronic, stable respiratory conditions who do not experience acute episodes may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more personalized and effective treatment strategies for patients suffering from acute dyspnea.
How similar studies have performed: Other research has shown promise in using machine learning approaches for treatment optimization, indicating potential success for this novel application.
Where this research is happening
Ann Arbor, United States
- University of Michigan at Ann Arbor — Ann Arbor, United States (Active)
Researchers
- Principal investigator: Wiens, Jenna — University of Michigan at Ann Arbor
- Study coordinator: Wiens, Jenna
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.