AI-powered echocardiography to spot common heart defects in newborns

Who could benefit from this research

What this research studies

This project aims to create AI models that can automatically detect five common acyanotic congenital heart defects (ASD, VSD, AVSD, COA, PDA) in infants using postnatal echocardiography. Building on prior work that automated basic cardiac view identification, the team will adapt models to recognize specific defects and landmarks, leveraging datasets from South Africa and Cameroon. The goal is to enable nurses, midwives, general practitioners, and sonographers in low-resource settings to screen for these conditions where specialists are scarce. The project will use convolutional neural networks to identify anatomical features and patterns associated with each CHD directly from echocardiogram videos. Overall, the work seeks to deliver a practical, point-of-care AI tool that supports earlier detection and timely referral for treatment.

Why it matters

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

Related research

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About this research

1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
3. For full project details, budget, and progress reports, visit the official NIH RePORTER page.