AI to Predict Memory and Thinking Problems After Stroke
Official title: Using AI on Routine Clinical and Imaging Data from Acute Stroke Encounter to Predict Post-Stroke Vascular Contributions to Cognitive Impairment (AI - RESPECT)
Funded at Emory University · NIH-11230049 · Data updated 2026-11-12
This project uses artificial intelligence to help doctors understand which stroke patients might develop memory and thinking problems, so they can receive better care.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Emory University NIH-funded |
| Lab location | 1 site (Atlanta, United States) |
| Project start | September 1, 2024 |
| Project end | July 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $234,750 |
| NIH project number | 3RF1NS139325-01S1 |
| Project ID | NIH-11230049 on NIH RePORTER |
Who could benefit from this research
✓Could help
This project focuses on individuals who have experienced an acute stroke and whose routine clinical and imaging data are available.
✕Less likely to help
Patients who have not experienced a stroke or do not have relevant clinical and imaging data would not directly benefit from this specific prediction tool.
What this research studies
Many people experience changes in their memory and thinking after a stroke, but these issues are often not recognized early enough. Our project aims to use AI to look at routine medical information and brain scans from stroke patients to identify those at high risk for these cognitive problems. By combining past patient records with new information from people who receive special memory tests, we hope to create a tool that can predict who needs extra support. This early prediction could help doctors create personalized recovery plans and prevent future strokes.
Why it matters
Potential benefit: If successful, this work could lead to earlier identification of post-stroke cognitive impairment, allowing for tailored care plans to improve patient recovery and prevent future health issues.
How similar studies have gone: While the use of AI in healthcare is growing, this specific application combining large retrospective and smaller prospective datasets to predict post-stroke cognitive impairment is a novel approach.
Where this research is happening
-
Emory University
Atlanta, United States Active
Researchers
- Principal investigator: Hu, Xiao — Emory University
- Study coordinator: Hu, Xiao
Related research
Other NIH-funded projects on the same topics.
-
Using AI to predict cognitive impairment after a stroke
This study is looking at how artificial intelligence can help doctors understand which stroke patients might have trouble with thinking and memory after their stroke, so they can get the right support to recover better.
-
Pericyte signaling in diabetic stroke-related cognitive problems
A patient-facing study exploring how blood vessel cells and inflammation after stroke interact in people with diabetes to influence cognitive decline and dementia.
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In-bed wearable rehab robot to help stroke survivors recover movement
A wearable robotic device will be developed to help adults who recently had an acute stroke regain movement while still in the hospital.
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When people are most at risk of another stroke after a minor stroke or TIA
Researchers are combining past trial data to find the timing of highest risk for a second stroke after a minor stroke or TIA so treatments can be better timed.
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Understanding and reducing cognitive problems after stroke
A study from the University of Michigan aims to see if simple cognitive activities and sleep improvements can lower the risk of developing vascular cognitive impairment and dementia after stroke.
-
Post-stroke cognitive decline and dementia: understanding and preventing PSCID
A large NIH project will use real-world data from two million stroke records to better understand how many people develop PSCID and what factors raise that risk, with the goal of guiding prevention and care.
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.