Machine learning to find new insights in archived childhood and adolescent development data
The promise of machine learning for novel approaches to archived developmental data
This project uses computer algorithms to find patterns in long-term data from people who had depression starting in childhood or adolescence to better understand risks and protections.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pittsburgh at Pittsburgh NIH-funded |
| Lab location | 1 site (Pittsburgh, United States) |
| Project ID | NIH-11143937 on NIH RePORTER |
What this research studies
This project will analyze long-term research data collected from people like you who had depression beginning in childhood or adolescence. The team is building machine learning tools to search repeated assessments taken from ages about 7–14 up through the late 20s and early 30s for patterns across symptoms, functioning, and biological measures. The archived dataset includes affected participants as well as biological siblings and control participants, all stored in the National Data Archive. The aim is to identify which risk and protective factors best predict long-term clinical and functional outcomes so future care can be more targeted.
Who could benefit from this research
Good fit: People whose depression began in childhood or adolescence (and family members included in the archived records) are the main group this work focuses on.
Not a fit: People without a history of childhood- or adolescent-onset depression or with unrelated medical issues may not directly benefit from these findings.
Why it matters
Potential benefit: If successful, this work could help identify who is most likely to have ongoing problems after childhood-onset depression and guide earlier, more personalized support.
How similar studies have performed: Some prior studies have used machine learning on psychiatric datasets with promising results, but applying these methods to long-term archives of childhood-onset depression is relatively new.
Where this research is happening
Pittsburgh, United States
- University of Pittsburgh at Pittsburgh — Pittsburgh, United States (Active)
Researchers
- Principal investigator: Kovacs, Maria — University of Pittsburgh at Pittsburgh
- Study coordinator: Kovacs, Maria
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.