Using computer methods to understand disease differences and improve risk assessment
Official title: Computational approaches to characterize heterogeneity and improve risk stratification in complex disease phenotypes
Funded at University of Colorado Denver · NIH-11080195 · Data updated 2026-11-12
This study is looking at how to use computer technology to better understand asthma by analyzing different health and genetic information, so we can find out what makes each person’s experience with the disease unique and help create more personalized treatments for everyone, especially those from different backgrounds.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Colorado Denver NIH-funded |
| Lab location | 1 site (Aurora, UNITED STATES) |
| Project start | May 12, 2023 |
| Project end | April 30, 2026 |
| Funding year | 2025 |
| Award (this year) | $249,000 |
| NIH project number | 5R00HG011898-04 |
| Project ID | NIH-11080195 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals with asthma or other complex diseases who come from diverse genetic backgrounds.
✕Less likely to help
Patients with single-gene disorders or those not affected by complex diseases may not benefit from this research.
What this research studies
This research focuses on leveraging advanced computational techniques to analyze diverse clinical and genetic data, aiming to better understand the complexities of diseases like asthma. By developing machine learning methods, the project seeks to identify specific risk factors and improve the accuracy of disease predictions for individuals. The goal is to enhance personalized treatment approaches by addressing the unique genetic and phenotypic variations among patients. This research also aims to reduce health disparities by including diverse population ancestries in its analysis.
Why it matters
Potential benefit: If successful, this research could lead to more accurate risk assessments and personalized treatment options for patients with complex diseases.
How similar studies have gone: Other research has shown promise in using computational methods for disease characterization, indicating that this approach could yield significant advancements.
Where this research is happening
-
University of Colorado Denver
Aurora, United States Active
Researchers
- Principal investigator: Pividori, Milton — University of Colorado Denver
- Study coordinator: Pividori, Milton
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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.