Using AI to predict and discover biomarkers for Alzheimer's disease
Official title: Convolutional Neural Network for Disease Prediction, Biomarker Discovery, and Validation in Alzheimer's Disease
Funded at University of Nevada Las Vegas · NIH-10875812 · Data updated 2026-11-12
This study is exploring how advanced computer technology can help predict Alzheimer's disease by turning genetic information into images, which could lead to better early diagnosis and treatment for people at risk.
Quick facts
| Grant type | R15 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Nevada Las Vegas NIH-funded |
| Lab location | 1 site (Las Vegas, United States) |
| Project start | June 1, 2024 |
| Project end | May 31, 2027 |
| Funding year | 2024 |
| Award (this year) | $447,509 |
| NIH project number | 1R15AG083618-01A1 |
| Project ID | NIH-10875812 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals with a family history of Alzheimer's disease or those showing early signs of cognitive decline.
✕Less likely to help
Patients with advanced Alzheimer's disease or those without any genetic predisposition to the condition may not benefit from this research.
What this research studies
This research focuses on developing advanced artificial intelligence techniques, specifically convolutional neural networks (CNNs), to predict Alzheimer's disease and identify potential biomarkers. By transforming genetic data into images, the study aims to leverage machine learning to improve early diagnosis and intervention strategies for individuals at risk of Alzheimer's. The approach combines genetic information with innovative AI methods to enhance understanding of the disease's complexities.
Why it matters
Potential benefit: If successful, this research could lead to earlier detection and better management of Alzheimer's disease, potentially improving patient outcomes.
How similar studies have gone: Other research has shown promise in using AI and machine learning for disease prediction, indicating that this approach could yield significant insights.
Where this research is happening
-
University of Nevada Las Vegas
Las Vegas, United States Active
Researchers
- Principal investigator: Chen, Jingchun — University of Nevada Las Vegas
- Study coordinator: Chen, Jingchun
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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.