Multimodal AI to improve genetic diagnosis of congenital heart disease
Official title: Multimodal AI for Precise Clinical and Genetic Diagnosis of Congenital Heart Disease
Funded at Baylor College of Medicine · NIH-11625643 · Data updated 2026-11-12
A new AI tool uses multiple types of patient data to help doctors find genetic causes of congenital heart disease more accurately.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Baylor College of Medicine NIH-funded |
| Lab location | 1 site (Houston, United States) |
| Project start | September 8, 2025 |
| Project end | September 7, 2027 |
| Funding year | 2026 |
| Award (this year) | $749,988 |
| NIH project number | 3OT2OD038054-01S2 |
| Project ID | NIH-11625643 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates include individuals with congenital heart disease undergoing genetic testing and data-rich clinical records (imaging, EMR, and genome data).
✕Less likely to help
Patients without comprehensive imaging/genetic data or those outside the CHD population may not benefit directly.
What this research studies
This project aims to combine imaging, genetic data, and medical records to prioritize genes and identify disease-causing variants in babies and patients with congenital heart disease. The approach will be designed with input from clinicians, families, and other stakeholders, and then integrated into an automated workflow. The goal is to speed up and improve the accuracy of genetic diagnoses that guide treatment and family planning. The work will address ethical considerations and test the AI system using real-world data from patients with heart defects.
Why it matters
Potential benefit: If successful, the tool could lead to faster, more precise genetic diagnoses and better-informed treatment decisions for children with CHD.
How similar studies have gone: Previous AI efforts in genetics show promise, but this multimodal integration is still emerging and could offer substantial new benefits.
Where this research is happening
-
Baylor College of Medicine
Houston, United States Active
Researchers
- Principal investigator: Milosavljevic, Aleksandar — Baylor College of Medicine
- Study coordinator: Milosavljevic, Aleksandar
Related research
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Multimodal AI to improve genetic diagnosis of congenital heart disease
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This grant studies how genetic differences contribute to congenital heart defects (CHD) and how these variations affect health over time, with patient data from a large biobank and health records.
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.