Using machine learning to improve diagnosis of Alzheimer's disease and related dementias
Official title: Profiling and forecasting individual unique progression in ADRD using machine learning
Funded at Massachusetts General Hospital · NIH-11131996 · Data updated 2026-11-12
This study is looking to improve how we spot Alzheimer's and related dementias early by using smart technology to collect information from wearables and conversations, helping us create a personalized way to predict when someone might get diagnosed.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Massachusetts General Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | June 15, 2025 |
| Project end | March 31, 2030 |
| Funding year | 2025 |
| Award (this year) | $129,330 |
| NIH project number | 1K01AG088184-01A1 |
| Project ID | NIH-11131996 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals showing early signs of cognitive decline or those at risk for Alzheimer's disease and related dementias.
✕Less likely to help
Patients with advanced stages of Alzheimer's disease or those who do not exhibit any symptoms of cognitive decline may not benefit from this research.
What this research studies
This research aims to enhance the early detection of Alzheimer's disease and related dementias (ADRD) by utilizing machine learning techniques. It will gather a variety of data, including digital biomarkers from wearables and acoustic markers from recorded conversations, to create a comprehensive profile of individual patient progression. By analyzing this diverse data, the research seeks to develop a risk prediction model that can accurately forecast the time to diagnosis for patients. This approach addresses the significant variability in how ADRD manifests in different individuals, aiming for more personalized and timely interventions.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of Alzheimer's disease and related dementias, allowing for timely interventions.
How similar studies have gone: Previous research has shown promise in using machine learning and multi-modal data for improving diagnostic accuracy in similar conditions, indicating a potential for success in this approach.
Where this research is happening
-
Massachusetts General Hospital
Boston, United States Active
Researchers
- Principal investigator: Wu, Chao-Yi — Massachusetts General Hospital
- Study coordinator: Wu, Chao-Yi
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.