Developing software to improve environmental health modeling using AI
Official title: Geostatistical Software for Non-Parametric Geostatistical Modeling of Uncertainty
Funded at Biomedware · NIH-11006986 · Data updated 2026-11-12
This study is working on smart software that uses artificial intelligence to help understand how things in our environment can affect our health, so that patients and communities can make better choices to stay safe and healthy.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Biomedware NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project start | September 15, 2023 |
| Project end | July 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $991,154 |
| NIH project number | 2R44LM014519-02 |
| Project ID | NIH-11006986 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals living in areas affected by environmental health risks, such as air pollution or hazardous materials.
✕Less likely to help
Patients who are not exposed to environmental health risks or who do not reside in affected communities may not benefit from this research.
What this research studies
This research focuses on creating advanced software that utilizes artificial intelligence to enhance the modeling of environmental health risks. By integrating various types of secondary data, the software aims to provide accurate predictions and insights into how environmental factors affect health outcomes. The approach combines geostatistics with machine learning to analyze spatial data, allowing for better decision-making and risk assessment. Patients and communities can benefit from improved understanding and management of health risks related to environmental exposures.
Why it matters
Potential benefit: If successful, this research could lead to more accurate assessments of environmental health risks, ultimately improving public health outcomes.
How similar studies have gone: Other research has shown success in using AI and geostatistical methods for environmental health modeling, indicating a promising approach.
Where this research is happening
-
Biomedware
Ann Arbor, United States Active
Researchers
- Principal investigator: Goovaerts, Pierre E — Biomedware
- Study coordinator: Goovaerts, Pierre E
Related research
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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.