Personalized prevention for perinatal depression using machine learning
SCH: Machine learning for personalized preventative intervention in perinatal depression
Using machine learning, this project will match pregnant people and new parents with the right preventive mental-health support before depression starts.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Carnegie-Mellon University NIH-funded |
| Lab location | 1 site (Pittsburgh, United States) |
| Project ID | NIH-11175529 on NIH RePORTER |
What this research studies
You may be asked to share health, behavior, or symptom information and to join interviews about your pregnancy or postpartum experience while researchers combine that with existing medical data to train computer models. The team will work closely with clinicians and people with lived experience to make sure recommendations are clear, fair, and relevant. The project will build tools that suggest which preventive supports to try first and update choices over time using adaptive experiments. The aim is to create scalable, understandable, and individualized prevention options that could be offered in routine care.
Who could benefit from this research
Good fit: Ideal participants are pregnant people or new parents at risk for perinatal depression, including those with prior depression, current symptoms, or other known risk factors.
Not a fit: People who are not pregnant or postpartum, those already experiencing severe, immediate depression requiring urgent treatment, or those unwilling to share health information may not receive direct benefit from this prevention-focused work.
Why it matters
Potential benefit: If successful, this could help identify people at risk earlier and direct them to the specific support most likely to prevent perinatal depression.
How similar studies have performed: Some prior work has used machine learning to predict postpartum depression risk, but applying ML to select and adapt personalized preventive treatments is relatively new and not yet proven at scale.
Where this research is happening
Pittsburgh, United States
- Carnegie-Mellon University — Pittsburgh, United States (Active)
Researchers
- Principal investigator: Wilder, Bryan — Carnegie-Mellon University
- Study coordinator: Wilder, Bryan
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 below.