Improving fetal growth assessment using maternal genetics and AI
Official title: Individualization of Fetal Growth Assessment using Maternal Genetics and Explainable AI
Funded at University of Utah · NIH-10784285 · Data updated 2026-11-12
This study is looking to improve how we track baby growth during pregnancy by using mom's genetic information and smart technology, helping to spot any potential growth issues early on for a healthier outcome.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Utah NIH-funded |
| Lab location | 1 site (Salt Lake City, United States) |
| Project start | July 1, 2024 |
| Project end | October 31, 2027 |
| Funding year | 2024 |
| Award (this year) | $171,720 |
| NIH project number | 1K08HD113835-01 |
| Project ID | NIH-10784285 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are pregnant individuals, particularly those with a family history of fetal growth issues or other related complications.
✕Less likely to help
Patients who are not currently pregnant or those without any risk factors for fetal growth restriction may not benefit from this research.
What this research studies
This research focuses on enhancing the assessment of fetal growth by integrating maternal genetic information with advanced artificial intelligence techniques. The goal is to develop a more personalized approach to identify fetuses at risk for growth restrictions, which can lead to serious complications. By utilizing programming skills and novel biomedical informatics, the research aims to create tools that can better predict adverse outcomes during pregnancy. This work is led by Dr. Nathan Blue, who is collaborating with experts in maternal-fetal medicine and genetics.
Why it matters
Potential benefit: If successful, this research could lead to improved prenatal care and reduced risks of stillbirth and other complications related to fetal growth restriction.
How similar studies have gone: Previous research has shown promise in using AI and genetic information for health assessments, indicating potential success for this novel approach.
Where this research is happening
-
University of Utah
Salt Lake City, United States Active
Researchers
- Principal investigator: Blue, Nathan Richard — University of Utah
- Study coordinator: Blue, Nathan Richard
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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.