Using advanced AI to find early signs of Alzheimer's disease
Official title: IDEAL-XAI: Advancing Explainable AI to Identify Early Driver Events of Alzheimer's Disease
Funded at University of Washington · NIH-10942708 · Data updated 2026-11-12
This study is looking to improve how we use artificial intelligence to better understand the early changes in brain cells that lead to Alzheimer's disease, which could help us find ways to detect it sooner and develop new treatments for patients.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Washington NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project start | August 15, 2024 |
| Project end | July 31, 2027 |
| Funding year | 2024 |
| Award (this year) | $1,761,543 |
| NIH project number | 1RF1AG088824-01 |
| Project ID | NIH-10942708 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals at risk for Alzheimer's disease or those in the early stages of cognitive decline.
✕Less likely to help
Patients with advanced Alzheimer's disease or those with other forms of dementia may not benefit from this research.
What this research studies
This research aims to enhance explainable artificial intelligence (XAI) to better understand the early cellular changes that lead to Alzheimer's disease. By analyzing single-cell data from various donor cohorts, the project seeks to identify key biological factors that contribute to the disease's progression. The approach involves developing machine learning models that can interpret complex datasets and provide insights into the underlying mechanisms of Alzheimer's. This could lead to earlier detection and potentially new therapeutic strategies for patients.
Why it matters
Potential benefit: If successful, this research could lead to earlier diagnosis and more effective treatments for Alzheimer's disease.
How similar studies have gone: Previous research has shown promise in using machine learning approaches to analyze Alzheimer's data, indicating potential for success in this novel application.
Where this research is happening
-
University of Washington
Seattle, United States Active
Researchers
- Principal investigator: Lee, Su-in — University of Washington
- Study coordinator: Lee, Su-in
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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.