Using machine learning to identify children at risk for autism and ADHD early
Official title: Machine Learning Methods to Develop and Deploy Real-Time Risk Surveillance for Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder from the Electronic Health Record
Funded at Duke University · NIH-10918192 · Data updated 2026-11-12
This study is looking to help doctors spot kids who might be at risk for autism or ADHD earlier by using information from their health records, so they can get the right support sooner.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Duke University NIH-funded |
| Lab location | 1 site (Durham, United States) |
| Project start | September 1, 2022 |
| Project end | August 31, 2027 |
| Funding year | 2024 |
| Award (this year) | $171,146 |
| NIH project number | 5K01MH127309-03 |
| Project ID | NIH-10918192 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are children aged 0-11 years who may be at risk for autism spectrum disorder or attention-deficit hyperactivity disorder.
✕Less likely to help
Patients who are already diagnosed with ASD or ADHD may not benefit directly from this research.
What this research studies
This research aims to improve the early identification of children at risk for autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) by utilizing data from electronic health records (EHR). By analyzing early health system utilization patterns and risk factors, the study will develop predictive models that can help clinicians make informed decisions about early interventions. The approach focuses on optimizing prediction accuracy while considering the balance between early identification and the need for additional data. Ultimately, this research seeks to enhance screening processes and improve outcomes for affected children.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate identification of children at risk for ASD and ADHD, allowing for timely interventions that improve long-term developmental outcomes.
How similar studies have gone: Previous research has shown promise in using electronic health record data for early identification of ASD and ADHD, indicating that this approach has potential for success.
Where this research is happening
-
Duke University
Durham, United States Active
Researchers
- Principal investigator: Engelhard, Matthew Morrow — Duke University
- Study coordinator: Engelhard, Matthew Morrow
Related research
Other NIH-funded projects on the same topics.
-
Understanding brain signals in autism to identify biologically distinct subtypes
This study uses EEG to link how the brain processes sensory information with behavior in young children with autism and related concerns.
-
Paternal exposures and sperm epigenetics linked to autism in children
This project looks at how a father's environment and health before conception might influence autism risk in his children.
-
Anxiety Management for Young Children with Autism
A study at a major hospital will test a medication called buspirone in young children with autism to see if it helps reduce anxiety.
-
Sleep problems in autism and daily functioning
A large study at a major university is looking at how sleep problems affect children with autism and their daily lives.
-
Sleep and ASD: Understanding how sleep problems relate to autism symptoms
A Stanford team is studying whether sleep problems contribute to and worsen autism symptoms in children and how improving sleep could help.
-
Canine-assisted addition to group therapy for emotion dysregulation in kids with autism
A study will test whether adding animal-assisted therapy to a proven group treatment helps reduce emotion dysregulation in children with autism.
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.