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Unravel the complexity in mental health prescribing
Optimizing prediction of response to antidepressant medications using machine learning and environmental data
This paper presents the assembly process of an algorithm that predicts individual response to antidepressants based on integrated genetic, clinical and demographic data, and its performance on validation and testing datasets.
A New Characterization of Mental Health Disorders Using Digital Behavioral Data: Evidence from Major Depressive Disorder
This medical opinion paper explains how digital behavioral data can help better characterize mental health disorders and advance personalized psychiatry.
Optimizing prediction of response to antidepressant medications using machine learning and integrated genetic, clinical, and demographic data
This abstract presents the assembly process of an algorithm that predicts individual response to antidepressants based on clinical and demographic data, and its performance on validation and testing datasets.
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