AI-assisted ultrasound to manage twin pregnancies in limited-resource settings
Official title: Assessment of Twin Gestation with AI-Assisted Ultrasound
Funded at Univ of North Carolina Chapel Hill · NIH-11402836 · Data updated 2026-11-12
A new AI-powered ultrasound tool aims to help providers in low-resource areas diagnose and monitor twin pregnancies using affordable, portable devices.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Univ of North Carolina Chapel Hill NIH-funded |
| Lab location | 1 site (Chapel Hill, United States) |
| Project start | September 1, 2025 |
| Project end | May 31, 2030 |
| Funding year | 2026 |
| Award (this year) | $537,131 |
| NIH project number | 5R01HD116891-02 |
| Project ID | NIH-11402836 on NIH RePORTER |
Who could benefit from this research
✓Could help
Pregnant people in resource-constrained settings or rural areas who are at risk for or experiencing twin gestations.
✕Less likely to help
Patients in settings with reliable access to conventional ultrasound may not directly benefit beyond standard care.
What this research studies
This project focuses on using point-of-care ultrasound and deep learning to identify twins, estimate gestational age, determine chorionicity, and track growth in twin pregnancies. It targets clinics with limited access to traditional obstetric ultrasound by providing a user-friendly protocol that can be used by non-specialists. The aim is to deliver five practical tools that work together to improve decision-making and maternal-fetal care in resource-constrained settings.
Why it matters
Potential benefit: If successful, the tools could lead to earlier detection and better management of twin pregnancies, improving outcomes for mothers and babies.
How similar studies have gone: Previous work shows promise for AI-assisted ultrasound in improving diagnostic speed and accuracy, but integration in low-resource settings is still developing.
Where this research is happening
-
Univ of North Carolina Chapel Hill
Chapel Hill, United States Active
Researchers
- Principal investigator: Stringer, Jeffrey Samuel Allen — Univ of North Carolina Chapel Hill
- Study coordinator: Stringer, Jeffrey Samuel Allen
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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.