Improving health outcomes using advanced machine learning tools for complex data analysis.
Official title: Enhanced Machine Learning Tools for Complex Data Evaluation and Integration in Advancing Health Outcomes
Funded at Univ of North Carolina Chapel Hill · NIH-11046860 · Data updated 2026-11-12
This study is looking at how to use smart computer techniques to better understand heart, lung, blood, and sleep problems, so that we can find better ways to diagnose and treat these conditions for patients like you.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Univ of North Carolina Chapel Hill NIH-funded |
| Lab location | 1 site (Chapel Hill, United States) |
| Project start | December 15, 2024 |
| Project end | November 30, 2028 |
| Funding year | 2025 |
| Award (this year) | $641,544 |
| NIH project number | 1R01HL173044-01A1 |
| Project ID | NIH-11046860 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals diagnosed with heart, lung, blood, or sleep disorders, as well as those at risk for these conditions.
✕Less likely to help
Patients with unrelated health issues or those not affected by heart, lung, blood, or sleep disorders may not receive any benefit from this research.
What this research studies
This research focuses on enhancing the analysis of complex health data related to heart, lung, blood, and sleep disorders. By utilizing advanced machine learning techniques, the project aims to better understand the intricate relationships between various health factors and disease outcomes. The goal is to develop more effective interventions and management strategies for these prevalent health issues. Patients may benefit from improved diagnostic and treatment approaches derived from this comprehensive data analysis.
Why it matters
Potential benefit: If successful, this research could lead to more effective treatments and management strategies for patients suffering from heart, lung, blood, and sleep disorders.
How similar studies have gone: Previous research has shown that advanced machine learning approaches can significantly improve the analysis of complex biomedical data, indicating a promising potential for this novel approach.
Where this research is happening
-
Univ of North Carolina Chapel Hill
Chapel Hill, United States Active
Researchers
- Principal investigator: Zou, Baiming — Univ of North Carolina Chapel Hill
- Study coordinator: Zou, Baiming
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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.