A system using machine learning to monitor and predict fetal health issues.
Official title: A machine learning based fetal monitoring system to predict and prevent fetal hypoxia.
Funded at Delfina Care INC. · NIH-10760437 · Data updated 2026-11-12
This study is working on a smart system that uses technology to help doctors keep an eye on babies during labor, aiming to spot any signs of trouble early on to keep them safe and healthy.
Quick facts
| Grant type | Sbir 1 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Delfina Care INC. NIH-funded |
| Lab location | 1 site (San Jose, UNITED STATES) |
| Project start | September 5, 2023 |
| Project end | August 31, 2025 |
| Funding year | 2023 |
| Award (this year) | $261,310 |
| NIH project number | 1R43HD113472-01 |
| Project ID | NIH-10760437 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are pregnant women who are in labor and at risk of fetal hypoxia.
✕Less likely to help
Patients who are not pregnant or those who are not in labor will not benefit from this research.
What this research studies
This research aims to develop a machine learning-based fetal monitoring system that can accurately predict and prevent fetal hypoxia during labor. By analyzing a large dataset of fetal heart rate tracings and electronic health records, the project seeks to create a model that offers high sensitivity and specificity in detecting potential health risks. The approach involves validating this model through rigorous testing and user studies to ensure it enhances clinician performance in real-time monitoring. If successful, this system could significantly improve outcomes for newborns during delivery.
Why it matters
Potential benefit: If successful, this research could lead to better prediction and prevention of fetal hypoxia, ultimately reducing the risk of serious health issues for newborns.
How similar studies have gone: Other research has shown promise in using machine learning for fetal monitoring, but this specific approach is novel and aims to address existing limitations in current methods.
Where this research is happening
-
Delfina Care INC.
San Jose, United States Active
Researchers
- Principal investigator: Zell, Bonnie Lesley — Delfina Care INC.
- Study coordinator: Zell, Bonnie Lesley
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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.