AI-guided newborn heart ultrasound for congenital heart defect diagnosis in Sub-Saharan Africa
Official title: Artificial Intelligence assisted echocardiography to facilitate optimal image extraction for congenital heart defects diagnosis in Sub-Saharan Africa
Funded at Health Research Foundation · NIH-11167476 · Data updated 2026-11-12
Using AI to help local health workers capture clearer newborn heart ultrasound images so babies in Sub-Saharan Africa get quicker and more accurate diagnoses of congenital heart defects.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Health Research Foundation NIH-funded |
| Lab location | 1 site (Buea, CAMEROON) |
| Project start | September 20, 2023 |
| Project end | July 31, 2026 |
| Funding year | 2025 |
| Award (this year) | $205,407 |
| NIH project number | 5U01HL172179-03 |
| Project ID | NIH-11167476 on NIH RePORTER |
Who could benefit from this research
✓Could help
Newborns (0–4 weeks old) born at or screened in participating hospitals or clinics in Sub-Saharan Africa, especially those with abnormal pulse oximetry or signs of heart problems.
✕Less likely to help
Older children, adults, infants outside participating sites, or babies with conditions not detectable by echocardiography are unlikely to benefit directly.
What this research studies
If your baby is born at a participating hospital, this project uses AI software to guide health workers to take the right ultrasound pictures of the heart. The AI helps extract the best images from scans and highlights findings that may indicate a congenital heart defect for remote expert review. This approach aims to reduce long, risky trips to distant pediatric cardiology centers and speed up confirmation after an abnormal pulse oximetry screen. The AI tool is designed to complement training so improvements persist despite staff turnover.
Why it matters
Potential benefit: Faster, more accurate newborn heart diagnoses closer to home, which could reduce dangerous travel and delays in treatment.
How similar studies have gone: Training programs and some AI-assisted echocardiography efforts have improved image capture and remote diagnosis elsewhere, but applying AI for newborn CHD detection in Sub-Saharan Africa is a relatively new application.
Where this research is happening
-
Health Research Foundation
Buea, Cameroon Active
Researchers
- Principal investigator: Leke, Aminkeng Zawuo — Health Research Foundation
- Study coordinator: Leke, Aminkeng Zawuo
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AI help for newborn heart ultrasound images in Sub‑Saharan Africa
This project uses AI to help health workers capture better heart ultrasound images so newborns in Sub‑Saharan Africa can get quicker, more accurate diagnosis of congenital heart defects.
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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.