This Project Grant award of $508,500 from the National Institute of Mental Health (NIMH), under the agency's Mental Health Research Grants program (CFDA 93.242), will support New York University (NYU) School of Medicine in conducting research to leverage electronic health records and advanced data analytics to develop predictive models and discover novel subtypes for psychosis-related disorders.
The key objectives of the 5-year project are to: 1) Leverage longitudinal electronic health record databases to build machine learning models to forecast major clinical outcomes like treatment response, illness severity, medical comorbidities, and diagnostic transitions in psychosis-related disorders; 2) Enhance these predictive models through dimensional phenotyping and whole genome sequencing of a 10,000-patient cohort; and 3) Explore the psychosocial and ethical implications of implementing such clinical outcome predictors in psychiatric care. The findings are expected to advance the goals of precision psychiatry by enabling more individualized treatment planning, outcome monitoring, and preventive interventions.
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