Using machine learning to detect Alzheimer's disease in veterans
Official title: Combining Machine Learning Methods and Scalable In Vivo Biomarkers for the Early and Accurate Detection of Alzheimer's Disease in Veterans
Funded at VA Boston Health Care System · NIH-10918753 · Data updated 2026-11-12
This study is working on a new, easy way to help veterans find out if they have Alzheimer's disease early on, using smart technology and simple tests, so they can get the right care before their memory starts to fade.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | VA Boston Health Care System NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | January 1, 2025 |
| Project end | December 31, 2029 |
| Funding year | 2025 |
| NIH project number | 1IK2CX002625-01A2 |
| Project ID | NIH-10918753 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are veterans who are experiencing cognitive changes or are at risk for Alzheimer's disease.
✕Less likely to help
Patients who are not veterans or those who do not exhibit any cognitive symptoms may not benefit from this research.
What this research studies
This research focuses on improving the early detection of Alzheimer's disease (AD) in veterans by utilizing machine learning techniques combined with easily accessible in vivo biomarkers. The goal is to create a cost-effective and convenient tool that can identify AD pathology before significant cognitive decline occurs. By analyzing data from routine clinical neuropsychological tests and digital assessments, the project aims to enhance diagnostic accuracy and provide veterans with timely access to necessary treatments and services. The study will leverage existing data from veterans who have undergone advanced imaging to develop predictive models.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of Alzheimer's disease in veterans, allowing for timely interventions and improved patient outcomes.
How similar studies have gone: While machine learning approaches have shown promise in other populations, this specific application within a veteran cohort is novel and has not been extensively tested.
Where this research is happening
-
VA Boston Health Care System
Boston, United States Active
Researchers
- Principal investigator: Frank, Brandon Edward — VA Boston Health Care System
- Study coordinator: Frank, Brandon Edward
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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.