Using machine learning to detect and prevent suicide in military personnel and veterans
Official title: A longitudinal machine learning approach providing clinicians timely detection to prevent military suicide
Funded at University of Illinois at Urbana-Champaign · NIH-10930092 · Data updated 2026-11-12
This study is working to help U.S. military members and veterans by using technology to predict who might be at risk for suicide, so they can get the right support before things get too serious.
Quick facts
| Grant type | R03 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Illinois at Urbana-Champaign NIH-funded |
| Lab location | 1 site (Champaign, United States) |
| Project start | September 30, 2023 |
| Project end | September 29, 2025 |
| Funding year | 2024 |
| Award (this year) | $49,410 |
| NIH project number | 5R03HS029557-02 |
| Project ID | NIH-10930092 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include active military service members and veterans who may be at risk for suicide.
✕Less likely to help
Patients who are not affiliated with the military or veterans' community may not receive any benefit from this research.
What this research studies
This research aims to address the high rates of suicide among U.S. military service members and veterans by developing a machine learning model that can predict suicide risk. By analyzing secondary datasets, the study will identify personalized risk factors and create early screening tools to intervene before a crisis occurs. The approach focuses on understanding the nuances of suicide ideation rather than just completed suicides, aiming to improve healthcare quality for military populations. Patients may benefit from more timely and effective interventions based on their unique risk profiles.
Why it matters
Potential benefit: If successful, this research could lead to improved prevention strategies that significantly reduce suicide rates among military personnel and veterans.
How similar studies have gone: While there have been various approaches to suicide prevention, the use of machine learning in this specific context is relatively novel and has not been extensively tested.
Where this research is happening
-
University of Illinois at Urbana-Champaign
Champaign, United States Active
Researchers
- Principal investigator: Chiu, Chung-Yi — University of Illinois at Urbana-Champaign
- Study coordinator: Chiu, Chung-Yi
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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.