Using AI to predict outcomes in acute stroke patients
Predicting Tissue and Functional Outcome in Acute Stroke
This study is looking to improve how doctors quickly decide on the best treatment for stroke patients by using smart computer technology to combine brain scans and medical information, aiming to help patients get better care faster and safer.
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-10900566 on NIH RePORTER |
What this research studies
This research aims to enhance the selection process for stroke patients needing urgent treatment by utilizing advanced AI techniques. It focuses on integrating imaging data from MR and CT scans with clinical information to predict patient outcomes more accurately. By developing deep learning models, the project seeks to improve the triage process and treatment effectiveness for acute ischemic stroke patients. The research will also explore the safety and efficiency of these methods without the need for contrast imaging.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals experiencing acute ischemic stroke who require urgent medical intervention.
Not a fit: Patients with non-acute strokes or those who do not require endovascular thrombectomy may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more effective and timely treatments for stroke patients, potentially improving recovery outcomes.
How similar studies have performed: Other research has shown promise in using AI for medical imaging and patient outcome predictions, indicating a strong potential for success in this approach.
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.