Using advanced machine learning to improve understanding of heart disease risk factors.
Bayesian machine learning for causal inference with incomplete longitudinal covariates and censored survival outcomes
This study is looking at how different factors affect heart health in young adults, using advanced computer techniques to make sense of tricky data, so that doctors can give better advice on when to start blood pressure treatments.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Rutgers Biomedical and Health Sciences NIH-funded |
| Lab location | 1 site (Newark, UNITED STATES) |
| Project ID | NIH-11079497 on NIH RePORTER |
What this research studies
This research focuses on analyzing data from large population studies to better understand cardiovascular disease (CVD) risk factors, particularly in young adults. By employing Bayesian machine learning techniques, the project aims to address challenges related to incomplete data and complex causal relationships in health outcomes. Patients may benefit from improved guidelines on when to start antihypertensive treatments based on more accurate assessments of blood pressure thresholds. The research will involve pooling data from multiple cohorts to enhance the robustness of findings.
Who could benefit from this research
Good fit: Ideal candidates for this research are young adults who are at risk for hypertension or cardiovascular disease.
Not a fit: Patients who are not within the age range of young adults or those without risk factors for hypertension may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more effective prevention strategies for cardiovascular disease in young adults.
How similar studies have performed: Previous research using Bayesian methods in similar contexts has shown promise, indicating potential for success in this novel application.
Where this research is happening
Newark, UNITED STATES
- Rutgers Biomedical and Health Sciences — Newark, United States (Active)
Researchers
- Principal investigator: Hu, Liangyuan — Rutgers Biomedical and Health Sciences
- Study coordinator: Hu, Liangyuan
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.