Identifying different types of asthma in children using advanced machine learning techniques
Official title: Identifying pediatric asthma subtypes using novel privacy-preserving federated machine learning methods
Funded at University of Florida · NIH-10918182 · Data updated 2026-11-12
This study is looking at different types of asthma in kids to find out what makes each one unique, so we can create better, personalized treatments that take into account how social factors might affect their asthma.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Florida NIH-funded |
| Lab location | 1 site (Gainesville, United States) |
| Project start | September 1, 2023 |
| Project end | June 30, 2028 |
| Funding year | 2024 |
| Award (this year) | $677,396 |
| NIH project number | 5R01HL169277-02 |
| Project ID | NIH-10918182 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are children aged 0-11 years who have been diagnosed with asthma.
✕Less likely to help
Patients with asthma who are older than 11 years or do not have a confirmed diagnosis of asthma may not benefit from this research.
What this research studies
This research aims to better understand the various subtypes of asthma in children by utilizing innovative privacy-preserving federated machine learning methods. By analyzing large datasets from electronic health records, the study seeks to identify unique characteristics and triggers of asthma in pediatric patients. This approach allows for a more personalized treatment plan tailored to individual needs, potentially improving care for children with asthma. The research will focus on understanding how social factors influence asthma severity and treatment responses.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized asthma management strategies for children.
How similar studies have gone: Previous research has shown promise in using machine learning for medical classification, indicating potential success for this novel approach in asthma subtyping.
Where this research is happening
-
University of Florida
Gainesville, United States Active
Researchers
- Principal investigator: Fishe, Jennifer Noel — University of Florida
- Study coordinator: Fishe, Jennifer Noel
Related research
Other NIH-funded projects on the same topics.
-
Predicting and Preventing Asthma Exacerbations in Children Exposed to Air Pollution
A pediatric-focused project aims to predict which kids with asthma are most at risk for flare-ups when air pollution is high, so clinicians can prevent attacks.
-
BPAP in severe pediatric asthma: a new treatment pathway for kids in the ED
A clinical trial tests whether starting BPAP, a non-invasive breathing support, in the emergency department helps kids with severe asthma recover faster and use fewer critical-care resources.
-
T-helper 2-low asthma in children: finding biomarkers and understanding triggers
A mentored, five-year career development grant aims to improve diagnosis and understand the causes of T2LOW asthma in children.
-
Positive Affect and Asthma in Kids: A New Way to Help Teens Stick to Their Inhalers
A study at Chapman University aims to help children and teens with asthma use their inhaled medications more consistently by using positive psychology approaches.
-
Air pollution sensitivity in pediatric asthma
Kids with asthma may have worse symptoms on days with dirty air, and this project aims to predict and prevent those flare-ups using data from medical records, genetics, and the environment.
-
Urban rat exposure and pediatric asthma in inner-city children
This grant explores whether living near rats affects how bad asthma is for children in urban areas.
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.