Using AI to improve diagnosis and outcomes for mitral valve disease
Deep Learning Based Phenotyping and Outcomes Prediction for Valvular Heart Disease
This study is looking at how we can use advanced computer technology to better understand mitral valve disease, helping doctors spot early signs of problems in heart images so they can provide better care and treatment for patients like you.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Cedars-Sinai Medical Center NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project ID | NIH-11064070 on NIH RePORTER |
What this research studies
This research focuses on mitral valve disease, a condition affecting millions worldwide, and aims to enhance diagnosis and predict outcomes using advanced artificial intelligence techniques. By applying deep learning algorithms to echocardiography images, the study seeks to identify subtle changes in heart structure and function that may indicate early signs of serious complications. The approach involves analyzing large datasets to improve the accuracy of phenotyping and risk assessment for patients with mitral valve issues. Ultimately, this research aims to provide better insights into patient management and treatment options.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals diagnosed with mitral valve disease or those at risk due to factors like age, sex, diabetes, or hypertension.
Not a fit: Patients with no history of mitral valve disease or those who do not undergo echocardiography may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of mitral valve disease, potentially improving patient outcomes and reducing the risk of severe complications.
How similar studies have performed: Previous research has demonstrated the effectiveness of AI in analyzing medical imaging, suggesting that this approach has the potential for significant advancements in the field.
Where this research is happening
Los Angeles, United States
- Cedars-Sinai Medical Center — Los Angeles, United States (Active)
Researchers
- Principal investigator: Ouyang, David — Cedars-Sinai Medical Center
- Study coordinator: Ouyang, David
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.