Using machine learning to better detect hypertrophic cardiomyopathy from health records
Improving the Detection of Hypertrophic Cardiomyopathy Using Machine Learning Applied to Electronic Health Record Data
This study is working on using advanced computer technology to help find people who might have hypertrophic cardiomyopathy, a heart condition that often runs in families, even if they haven't been diagnosed yet, so they can get the care they need sooner.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pennsylvania NIH-funded |
| Lab location | 1 site (Philadelphia, United States) |
| Project ID | NIH-10910166 on NIH RePORTER |
What this research studies
This research focuses on improving the detection of hypertrophic cardiomyopathy, a common inherited heart condition, by utilizing machine learning techniques applied to electronic health record data. The goal is to identify individuals who may have this condition but have not yet been diagnosed, allowing for earlier intervention and treatment. The study will develop and validate diagnostic algorithms that analyze various health data to enhance detection rates. By leveraging data from multiple institutions, the research aims to create a more accurate and sensitive model for identifying at-risk patients.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals with a family history of hypertrophic cardiomyopathy or those showing symptoms related to heart conditions.
Not a fit: Patients who have already been diagnosed and are receiving appropriate treatment for hypertrophic cardiomyopathy may not benefit directly from this research.
Why it matters
Potential benefit: If successful, this research could lead to earlier diagnosis and treatment for individuals with hypertrophic cardiomyopathy, potentially reducing the risk of severe complications such as heart failure and sudden death.
How similar studies have performed: Previous research has shown promise in using machine learning for improving diagnostic accuracy in various medical conditions, suggesting that this approach could be effective for hypertrophic cardiomyopathy as well.
Where this research is happening
Philadelphia, United States
- University of Pennsylvania — Philadelphia, United States (Active)
Researchers
- Principal investigator: Reza, Nosheen — University of Pennsylvania
- Study coordinator: Reza, Nosheen
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.