Clearer, interpretable brain-scan tools for Alzheimer's and related dementias

SCH: Novel and Interpretable Statistical Learning for Brain Images in AD/ADRDs

NIH-funded research George Mason University · NIH-11310112

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 typeR01 grant
Study typeNIH-funded research
Funding institutionGeorge Mason University NIH-funded
Lab location1 site (Fairfax, United States)
Project IDNIH-11310112 on NIH RePORTER

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.

Who could benefit from this research

Good fit: 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.

Not a fit: 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.

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 performed: 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

Fairfax, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.