Whole Person and Population Modelling
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Discover the fundamental mechanisms of mental illness and develop precision tools to assist in medical decision making across the lifespan

Our Approach

We develop and apply new methodologies in machine learning to integrate data types from large population-level datasets spanning multi-scale genomic, neuroimaging, fluid biomarker, socio-demographic, environmental, cognitive, and clinical information

GENE X ENVIRONMENT INTERACTIONS

STRATIFIED POLYGENIC MODELING

PREDICTION OF TREATMENT RESPONSE

NETWORK-BASED INTEGRATION AND VISUALIZATION

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