Using collective intelligence and AI to predict risk of psychosis
Official title: Hive Mind: Harnessing Collective Intelligence for Predicting Clinical High-Risk for Psychosis Outcomes
Funded at Beth Israel Deaconess Medical Center · NIH-11134887 · Data updated 2026-11-12
This study is looking to help people at risk of developing psychotic disorders by using a mix of artificial intelligence and expert knowledge to better predict who might experience full-blown psychosis, so they can get early support and personalized treatments to improve their chances of recovery.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Beth Israel Deaconess Medical Center NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | April 1, 2025 |
| Project end | March 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $334,588 |
| NIH project number | 1R21MH137740-01A1 |
| Project ID | NIH-11134887 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals identified as being at clinical high-risk for psychosis, particularly those showing early signs of psychotic symptoms.
✕Less likely to help
Patients who have already developed full-blown psychotic disorders may not benefit from this research.
What this research studies
This research focuses on improving the prediction of clinical high-risk outcomes for individuals at risk of developing psychotic disorders. By combining artificial intelligence with human insights, the study aims to create a more accurate predictive model that can identify individuals who may convert to full psychosis. The approach emphasizes early intervention during a critical phase when the brain is vulnerable, potentially delaying or preventing the onset of psychosis. Participants may benefit from tailored therapies based on these predictions, enhancing their chances of recovery.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more effective interventions for individuals at high risk of developing psychosis.
How similar studies have gone: Previous research has shown promise in using AI for predictive analytics in psychiatry, but this specific hybrid approach incorporating collective intelligence is relatively novel.
Where this research is happening
-
Beth Israel Deaconess Medical Center
Boston, United States Active
Researchers
- Principal investigator: Yassine, Walid — Beth Israel Deaconess Medical Center
- Study coordinator: Yassine, Walid
Related research
Other NIH-funded projects on the same topics.
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Psychosis in diverse settings across the world
This project studies how psychotic disorders show up and respond to treatment in adults with diverse backgrounds, including populations in Africa, the Caribbean, and other Global South settings.
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Psychosis in Diverse Settings: Understanding Symptoms and Treatment Across Global South
A human-facing study will look at how psychotic disorders present and respond to treatment in adults from Africa, the Caribbean, and other Global South settings, using genetic and clinical data.
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A new online brain-scan-style tool to spot early psychosis risk
A new online-based set of tasks and a computer model aims to identify people at high risk for developing psychosis earlier and more accurately.
-
Genetic clues for early-onset psychosis in Latino youth
This project looks at the genes of young people with early-onset psychosis and compares them with similar youths without psychosis to find genetic factors that contribute to the illness.
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Biomarkers to tailor rehab for Veterans with schizophrenia
A clinician-scientist is developing a brain-based biomarker to guide personalized rehabilitation for Veterans with schizophrenia.
-
Computational analysis of facial expression in early psychosis
Aims to develop computer-based measures of facial expression in people at risk for or with schizophrenia to help track symptoms and guide future trials.
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.