Clearer, interpretable brain-scan tools for Alzheimer's and related dementias
Official title: SCH: Novel and Interpretable Statistical Learning for Brain Images in AD/ADRDs
Funded at George Mason University · NIH-11310112 · Data updated 2026-11-12
New computer methods will look for clear signs in 3D brain scans and genetic data to help people with Alzheimer's and related dementias.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | George Mason University NIH-funded |
| Lab location | 1 site (Fairfax, United States) |
| Project start | September 1, 2023 |
| Project end | April 30, 2027 |
| Funding year | 2026 |
| Award (this year) | $277,510 |
| NIH project number | 5R01AG085616-04 |
| Project ID | NIH-11310112 on NIH RePORTER |
Who could benefit from this research
✓Could help
People with Alzheimer's disease, related dementias, or older adults with cognitive concerns who can share brain scans, genetic samples, or clinical data would be the most relevant candidates to contribute.
✕Less likely to help
People without brain imaging or genetic data, or those with conditions unrelated to Alzheimer's or dementia, are unlikely to benefit directly from this work.
What this research studies
Researchers across several institutions will build easy-to-understand statistical learning tools that work directly with 3D and higher-dimensional brain imaging data. They will combine imaging with genetic and clinical information to find imaging-based biomarkers linked to Alzheimer's and related dementias. The team will focus on methods that handle large, noisy datasets, quantify uncertainty, and make results interpretable for clinicians. The work uses large-scale human brain imaging and genetic datasets and scalable computing tools to create biomarkers that could inform diagnosis, prognosis, and treatment decisions.
Why it matters
Potential benefit: If successful, this could produce clearer imaging and genetic biomarkers that improve diagnosis, predict decline, and help guide treatment choices for people with Alzheimer's and related dementias.
How similar studies have gone: Machine-learning approaches on brain scans have shown promise in Alzheimer's, but applying interpretable 3D imaging analysis together with genome-wide genetic data is relatively new and remains under active testing.
Where this research is happening
-
George Mason University
Fairfax, United States Active
Researchers
- Principal investigator: Wang, Lily — George Mason University
- Study coordinator: Wang, Lily
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.