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Building better biomarkers: Brain models in translational neuroimaging Highly Cited Paper

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Title
Building better biomarkers: Brain models in translational neuroimaging
Author(s)
Choong-Wan Woo; Luke J Chang; Martin A Lindquist; Tor D Wager
Publication Date
2017-03
Journal
NATURE NEUROSCIENCE, v.20, no.3, pp.365 - 377
Publisher
NATURE PUBLISHING GROUP
Abstract
Despite its great promise, neuroimaging has yet to substantially impact clinical practice and public health. However, a developing synergy between emerging analysis techniques and data-sharing initiatives has the potential to transform the role of neuroimaging in clinical applications. We review the state of translational neuroimaging and outline an approach to developing brain signatures that can be shared, tested in multiple contexts and applied in clinical settings. The approach rests on three pillars: (i) the use of multivariate pattern-recognition techniques to develop brain signatures for clinical outcomes and relevant mental processes; (ii) assessment and optimization of their diagnostic value; and (iii) a program of broad exploration followed by increasingly rigorous assessment of generalizability across samples, research contexts and populations. Increasingly sophisticated models based on these principles will help to overcome some of the obstacles on the road from basic neuroscience to better health and will ultimately serve both basic and applied goals. © 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
URI
https://pr.ibs.re.kr/handle/8788114/3753
ISSN
1097-6256
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > Journal Papers (저널논문)
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