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Computational psychiatry as a bridge from neuroscience to clinical applications

Computational psychiatry as a bridge from neuroscience to clinical applications The complexity of problems and data in psychiatry requires powerful computational approaches. Computational psychiatry is an emerging field encompassing mechanistic theory-driven models and theoretically agnostic data-driven analyses that use machine-learning techniques. Clinical applications will benefit from relating theoretically meaningful process variables to complex psychiatric outcomes through data-driven techniques. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Nature Neuroscience Springer Journals

Computational psychiatry as a bridge from neuroscience to clinical applications

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References (161)

Publisher
Springer Journals
Copyright
Copyright © 2016 by Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.
Subject
Biomedicine; Biomedicine, general; Neurosciences; Behavioral Sciences; Biological Techniques; Neurobiology; Animal Genetics and Genomics
ISSN
1097-6256
eISSN
1546-1726
DOI
10.1038/nn.4238
Publisher site
See Article on Publisher Site

Abstract

The complexity of problems and data in psychiatry requires powerful computational approaches. Computational psychiatry is an emerging field encompassing mechanistic theory-driven models and theoretically agnostic data-driven analyses that use machine-learning techniques. Clinical applications will benefit from relating theoretically meaningful process variables to complex psychiatric outcomes through data-driven techniques.

Journal

Nature NeuroscienceSpringer Journals

Published: Feb 23, 2016

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