Using wearable devices to improve health predictions and learning.
Official title: SCH: Individualized learning and prediction for heterogeneous multimodal data from wearable devices
Funded at University of California-Irvine · NIH-11064395 · Data updated 2026-11-12
This study is looking at how information from wearable devices can help us understand health trends and improve healthcare, especially for women and diverse groups, by using smart technology to predict health problems and create personalized solutions.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California-Irvine NIH-funded |
| Lab location | 1 site (Irvine, United States) |
| Project start | July 1, 2024 |
| Project end | June 30, 2028 |
| Funding year | 2024 |
| Award (this year) | $299,988 |
| NIH project number | 1R01CA297869-01 |
| Project ID | NIH-11064395 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include women from diverse ethnic backgrounds who use wearable health devices.
✕Less likely to help
Patients who do not use wearable devices or those who do not identify as women may not benefit from this research.
What this research studies
This research focuses on harnessing data from wearable devices to better understand health trends and outcomes, particularly among diverse populations. By analyzing complex and varied health data, the project aims to develop advanced machine learning models that can predict health issues and personalize healthcare solutions. The study emphasizes the importance of social factors affecting health, especially for women, and seeks to address disparities in health outcomes through innovative data analysis techniques.
Why it matters
Potential benefit: If successful, this research could lead to more personalized and effective healthcare solutions that reduce health disparities among women.
How similar studies have gone: Other research has shown promise in using machine learning with health data, but this approach specifically targeting diverse populations and social determinants is relatively novel.
Where this research is happening
-
University of California-Irvine
Irvine, United States Active
Researchers
- Principal investigator: Qu, Annie — University of California-Irvine
- Study coordinator: Qu, Annie
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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.