Precision Computational Psychiatry aims to leverage functional connectivity abnormalities
measured with resting state functional MRI (rfMRI) to develop objective clinical markers
of mental health. Advanced analysis methods are needed to account for widespread heterogeneity
observed in symptom profiles and in brain organization. We present a novel analysis
framework that is designed to robustly map brain-symptom associations from heterogeneous
large-scale imaging datasets.
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© 2020 Published by Elsevier Inc.
