Improving Stroke Treatment Decisions with AI
Predicting Tissue and Functional Outcome in Acute Stroke
This project is developing an advanced computer system to help doctors make faster and better decisions for patients experiencing a sudden stroke.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project ID | NIH-11177055 on NIH RePORTER |
What this research studies
When someone has a stroke, every minute counts, but current methods for deciding on the best treatment, like clot removal, are not always perfect. This project aims to create a new artificial intelligence (AI) system that can look at brain scans and other patient information to predict how a patient's brain tissue and overall function might recover. By training this AI with a lot of patient data, including different types of scans, we hope it can accurately estimate the best treatment path for each individual. The goal is to make these predictions quickly and safely, even without certain types of contrast imaging, and to ensure the system works well for diverse patient populations and different hospital settings.
Who could benefit from this research
Good fit: This work is focused on acute ischemic stroke patients who would typically undergo initial MR and CT imaging.
Not a fit: Patients who have not experienced an acute ischemic stroke or those not undergoing standard neuroimaging would not directly benefit from this specific AI tool.
Why it matters
Potential benefit: If successful, this AI system could lead to more precise and timely treatment decisions for stroke patients, potentially improving their recovery and reducing disability.
How similar studies have performed: Deep learning and AI have shown great promise in various medical applications, suggesting a strong foundation for this novel approach in stroke care.
Where this research is happening
Stanford, United States
- Stanford University — Stanford, United States (Active)
Researchers
- Principal investigator: Zaharchuk, Gregory George — Stanford University
- Study coordinator: Zaharchuk, Gregory George
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.