Predicting Psychosis Outcomes from Health Records
Official title: 2/5 Clinical Outcome Prediction of Psychosis from Electronic Health Records (COPPER)
Funded at New York Genome Center · NIH-11184424 · Data updated 2026-11-12
This project uses artificial intelligence to help predict future outcomes for people living with psychosis, aiming for more personalized care.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | New York Genome Center NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | September 6, 2024 |
| Project end | May 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $639,892 |
| NIH project number | 5R01MH137676-02 |
| Project ID | NIH-11184424 on NIH RePORTER |
Who could benefit from this research
✓Could help
This work is relevant for individuals diagnosed with schizophrenia and other psychosis-related disorders, as it uses their health data to understand disease progression.
✕Less likely to help
Patients without a diagnosis of psychosis-related disorders would not directly benefit from the specific predictions developed by this project.
What this research studies
We are developing new ways to predict how psychosis might progress for individuals, using information from their electronic health records, detailed symptom patterns, and genetic data. Our goal is to create tools that can help doctors make more informed decisions about treatment plans and resource allocation. We also plan to look at the social and ethical considerations of using these types of predictions in mental health care. This work aims to bring personalized medicine to psychiatry, helping to tailor treatments and monitor progress more effectively.
Why it matters
Potential benefit: If successful, this work could lead to more personalized treatment plans and better monitoring for individuals with psychosis, potentially improving long-term outcomes and reducing side effects.
How similar studies have gone: While clinical predictors are common in other medical fields, their application in psychiatry, especially for psychosis outcomes using machine learning on EHRs, is a relatively new and developing area.
Where this research is happening
-
New York Genome Center
New York, United States Active
Researchers
- Principal investigator: Zody, Michael C — New York Genome Center
- Study coordinator: Zody, Michael C
Related research
Other NIH-funded projects on the same topics.
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Psychosis in Diverse Settings: Understanding Symptoms and Treatment Across Global South
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A new online brain-scan-style tool to spot early psychosis risk
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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.
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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.