Using machine learning to create personalized prevention strategies for perinatal depression

SCH: Machine learning for personalized preventative intervention in perinatal depression

NIH-funded research Carnegie-Mellon University · NIH-11060670

This study is looking to use smart technology to create personalized support for people dealing with perinatal depression, helping to figure out who might need specific help the most, so they can get the best care during pregnancy and after.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionCarnegie-Mellon University NIH-funded
Lab location1 site (Pittsburgh, United States)
Project IDNIH-11060670 on NIH RePORTER

What this research studies

This research aims to harness machine learning to develop tailored preventative interventions for individuals experiencing perinatal depression, a condition affecting about 15% of pregnant individuals. By analyzing historical data and incorporating insights from both healthcare professionals and those with lived experiences, the project seeks to identify which patients would benefit most from specific interventions. The approach includes creating algorithms that can predict risk factors and guide personalized treatment plans, ultimately improving mental health care during the perinatal period.

Who could benefit from this research

Good fit: Ideal candidates for this research include pregnant individuals who are at risk for perinatal depression.

Not a fit: Patients who are not pregnant or who do not have risk factors for perinatal depression may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to more effective and personalized prevention strategies for perinatal depression, potentially reducing its incidence and associated risks.

How similar studies have performed: Previous research has shown promise in using machine learning for mental health interventions, indicating potential success for this novel approach.

Where this research is happening

Pittsburgh, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.