Developing new methods to analyze complex health data for better patient outcomes
New statistical methods and software for modeling complex multivariate survival data with large-scale covariates
This study is working on new ways to analyze health data to better understand conditions like Alzheimer's and age-related vision problems, so that doctors can give more personalized treatment recommendations based on each patient's unique situation.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pittsburgh at Pittsburgh NIH-funded |
| Lab location | 1 site (Pittsburgh, United States) |
| Project ID | NIH-11089332 on NIH RePORTER |
What this research studies
This research focuses on creating advanced statistical methods and software to analyze complex health data, particularly for conditions like Alzheimer's disease and age-related macular degeneration. By utilizing large-scale genetic and imaging data, the project aims to improve individualized risk prediction and precision medicine. The researchers will develop new models that can handle multivariate survival data, which is crucial for understanding how different health conditions interact and affect patient outcomes. This approach will help in accurately assessing the risks and benefits of treatments for patients with multiple health issues.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals diagnosed with Alzheimer's disease or age-related macular degeneration, particularly those with multiple co-existing health conditions.
Not a fit: Patients with single, uncomplicated health conditions may not receive significant benefits from this research.
Why it matters
Potential benefit: If successful, this research could lead to more personalized and effective treatment strategies for patients with complex health conditions.
How similar studies have performed: Previous research has shown promise in using advanced statistical methods for analyzing complex health data, indicating that this approach could yield valuable insights.
Where this research is happening
Pittsburgh, United States
- University of Pittsburgh at Pittsburgh — Pittsburgh, United States (Active)
Researchers
- Principal investigator: Ding, Ying — University of Pittsburgh at Pittsburgh
- Study coordinator: Ding, Ying
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 below.