Predicting Psychosis Outcomes Using Health Records

5/5 Clinical Outcome Prediction of Psychosis from Electronic Health Records (COPPER)

['FUNDING_R01'] · UNIVERSITY OF CHICAGO · NIH-11182538

This project uses artificial intelligence to help predict how psychosis might progress for individuals, aiming to personalize treatment plans.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF CHICAGO (nih funded)
Locations1 site (CHICAGO, UNITED STATES)
Trial IDNIH-11182538 on ClinicalTrials.gov

What this research studies

We are creating new tools using artificial intelligence to better understand and predict the long-term journey of psychosis. By looking at information from electronic health records, we hope to identify different patterns and types of psychosis. This approach could help doctors make more informed decisions about treatment and care, moving towards a future where each patient receives care tailored specifically for them. We are also considering the social and ethical aspects of using these new prediction tools in mental health.

Who could benefit from this research

Good fit: This research is relevant for individuals diagnosed with schizophrenia and other psychosis-related disorders, as it aims to improve their future care.

Not a fit: Patients without a diagnosis of psychosis-related disorders would not directly benefit from this specific research.

Why it matters

Potential benefit: If successful, this work could lead to more personalized treatment plans for individuals with psychosis, potentially reducing side effects and improving long-term outcomes.

How similar studies have performed: While clinical predictors are common in other medical fields, this approach is novel in applying advanced machine learning to large psychiatric health record databases for psychosis outcome prediction.

Where this research is happening

CHICAGO, 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.

View on NIH RePORTER →

Last reviewed 2026-05-15 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.