Using machine learning to improve detection of pulmonary embolism
Clinical Decision Support for Assessing Pulmonary Embolism using Machine Learning
This study is working on a new software that helps doctors quickly and accurately find blood clots in the lungs using routine CT scans, making it easier for patients to get the right treatment faster.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Minnesota Healthsolutions Corporation NIH-funded |
| Lab location | 1 site (Saint Paul, United States) |
| Project ID | NIH-10576273 on NIH RePORTER |
What this research studies
This research aims to develop a software tool that utilizes machine learning to automatically detect and stage pulmonary embolisms (PEs) from routine pulmonary CT angiograms. By integrating this tool into the existing radiology workflow, it seeks to enhance the accuracy and speed of PE diagnosis, which is crucial for timely treatment. The project combines advanced technology with clinical expertise to address the variability in detection rates among radiologists and improve patient outcomes in emergency departments.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients undergoing pulmonary CT angiograms who are at risk for pulmonary embolism.
Not a fit: Patients who do not require a CT angiogram or those with conditions unrelated to pulmonary embolism may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to faster and more accurate diagnoses of pulmonary embolism, potentially saving lives and improving treatment outcomes.
How similar studies have performed: Other research has shown success in using machine learning for medical imaging, indicating a promising potential for this approach in detecting pulmonary embolism.
Where this research is happening
Saint Paul, United States
- Minnesota Healthsolutions Corporation — Saint Paul, United States (Active)
Researchers
- Principal investigator: Kramer, Kevin M. — Minnesota Healthsolutions Corporation
- Study coordinator: Kramer, Kevin M.
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.