Improving predictions of disease progression using big data and advanced algorithms
Official title: Transforming Precision Medicine: Dynamic Learning and Prediction of Disease Progression in Massive, Diverse, and Multimodal Cohorts
Funded at University of California Los Angeles · NIH-11028636 · Data updated 2026-11-12
This study is looking at health records and other data to learn how diseases like diabetes change over time, so patients can get personalized insights to help manage their health better.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Los Angeles NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project start | March 10, 2025 |
| Project end | February 28, 2029 |
| Funding year | 2025 |
| Award (this year) | $562,589 |
| NIH project number | 1R01DK142026-01 |
| Project ID | NIH-11028636 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals with chronic conditions, particularly those at risk for complications related to diabetes.
✕Less likely to help
Patients with acute conditions or those not involved in long-term health monitoring may not benefit from this research.
What this research studies
This research focuses on harnessing large healthcare datasets, such as electronic medical records and biobanks, to better understand how diseases progress over time. By developing new statistical methods and computational algorithms, the project aims to analyze complex health data and identify risk factors associated with disease onset. Patients may benefit from personalized insights into their health trajectories, which could lead to more effective management of conditions like diabetes. The research will also create user-friendly software tools to facilitate this analysis.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of disease progression, enabling tailored treatment plans for patients.
How similar studies have gone: Previous research utilizing similar big data approaches has shown promise in improving disease management and prediction accuracy.
Where this research is happening
-
University of California Los Angeles
Los Angeles, United States Active
Researchers
- Principal investigator: Zhou, Jin — University of California Los Angeles
- Study coordinator: Zhou, Jin
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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.