This $480,834 Project Grant award from the National Institute of Mental Health (NIMH) under the Mental Health Research Grants (CFDA 93.242) program supports research to leverage electronic health records (EHRs) and genetic data to develop machine learning-based predictive models for key clinical outcomes in psychosis-related disorders. The primary objectives are to: 1) Build individual-level prediction models for treatment response, illness severity, medical comorbidities, and diagnostic...
This $287,000 Project Grant award from the National Institute of Mental Health (NIMH), under CFDA Program 93.242 Mental Health Research Grants, will enable the University of Chicago to leverage electronic health records and machine learning to develop predictive models for clinical outcomes in psychosis-related disorders. The key objectives are to:
Build individual-level predictive models for treatment response, illness severity, medical comorbidities, and diagnostic transitions in...
The National Institute of Mental Health (NIMH) awarded a $508,500 Project Grant under the Mental Health Research Grants program (CFDA 93.242) to New York University School of Medicine. The grant, titled "CLINICAL OUTCOME PREDICTION OF PSYCHOSIS FROM ELECTRONIC HEALTH RECORDS (COPPER)," aims to leverage machine learning approaches to build predictors and identify subtypes of clinical outcomes among individuals with schizophrenia. Key activities include:
Using two independent...
This Project Grant award from the National Institute of Mental Health (NIMH) under the Mental Health Research Grants program (CFDA 93.242) will leverage electronic health records, dimensional phenotyping, and genetic analyses to build machine learning-based models to predict clinical outcomes and identify subtypes among individuals with psychosis-related disorders. The $2,048,026 award to The Trustees of Columbia University in the City of New York will support the following key activities...
The National Institute of Mental Health (NIMH) awarded a $4,170,401 Cooperative Agreement (Grant ID U01MH136535) under the Mental Health Research Grants program (CFDA 93.242) to the Icahn School of Medicine at Mount Sinai. The goal of the "Phenotypes Reimagined to Define Clinical Treatment and Outcome Research (PREDICTOR)" project is to develop individualized clinical signatures to predict key mental health outcomes like treatment disengagement, ER visits, and hospitalizations. The...
This federal Project Grant award of $434,421 from the National Institute of Mental Health (NIMH) under the Mental Health Research Grants program (CFDA 93.242) supports research by The Feinstein Institutes for Medical Research to investigate the development of cerebellar-cortical functional connectivity in youth and its prediction of psychosis.
The key objectives of the research are to: 1) chart the normal developmental trajectories of cerebellar-cortical connectivity from childhood to early...
This National Institute of Mental Health (NIMH) Project Grant award under CFDA 93.242 Mental Health Research Grants will support the "COPPER" (Clinical Outcome Prediction of Psychosis from Electronic Health Records) research initiative. The $784,642 grant, awarded on September 6, 2024, will leverage longitudinal electronic health record data and apply machine learning to develop predictive models for key clinical outcomes in individuals with psychosis-related disorders, including...
The National Institute of Mental Health (NIMH) awarded a $436,004 Project Grant under the Mental Health Research Grants program (CFDA 93.242) to Mayo Clinic. The grant, titled "PSYCHEMERGE: ADVANCING PRECISION PSYCHIATRY," will extend the PsychEmerge network's foundational efforts to address barriers in scalability, utility of genomic data, clinical application, and translation to clinical practice in precision psychiatry. Key project objectives include:
Creating a nationwide...
The National Institute of Mental Health (NIMH) awarded a $782,271 Project Grant under the Mental Health Research Grants program (CFDA 93.242) to the University of California, Los Angeles (UCLA) to advance precision psychiatry through a collaborative, nationwide research initiative. The 5-year grant, running from September 1, 2024 to May 31, 2029, aims to develop generalizable and bias-aware machine learning algorithms, integrate state-of-the-art genomic and medical record analysis methods,...
The National Institute of Mental Health (NIMH) awarded a $4,159,108 Cooperative Agreement grant (CFDA 93.242 - Mental Health Research Grants) to Yale University on August 12, 2024. The "IMPACT-MH: Clinical and Behavioral Fingerprints of Psychopathology" project aims to collect longitudinal data from a large sample of individuals with a wide range of psychiatric diagnoses. The study will analyze this data using advanced statistical and machine learning techniques to identify...