AI help for newborn heart ultrasound images 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-11416254 · Data updated 2026-11-12
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.
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) | $29,196 |
| NIH project number | 3U01HL172179-03S1 |
| Project ID | NIH-11416254 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are newborn infants in Sub‑Saharan Africa who need a heart ultrasound because of suspected congenital heart defects or abnormal newborn screening results.
✕Less likely to help
Older children and adults, or infants already receiving specialist echocardiography at tertiary centers, are unlikely to benefit directly from this newborn-focused imaging tool.
What this research studies
From a parent's point of view, researchers are building AI software that guides or improves echocardiogram image capture and pulls out the best pictures for diagnosing congenital heart defects in newborns. The tool is intended to be used by local health workers who are not specialist pediatric cardiologists, working alongside training to make scans more reliable. Teams will pilot and refine the system at hospitals in Sub‑Saharan Africa (the lead site is in Buea, Cameroon), comparing AI-supported images and readings with expert interpretations. The aim is to shorten delays and reduce the need for long, risky travel to distant specialist centers.
Why it matters
Potential benefit: If successful, this could enable earlier and more accurate local diagnosis of newborn heart defects, lowering delays and the burden of travel for families.
How similar studies have gone: Related AI-assisted ultrasound and training programs have improved image capture and triage in other low-resource settings, but applying AI specifically for newborn congenital heart defects in Sub‑Saharan Africa is relatively new.
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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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.