Building better biomarkers: Brain models in translational neuroimagingHighly Cited Paper
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choong-Wan Woo | - |
dc.contributor.author | Luke J Chang | - |
dc.contributor.author | Martin A Lindquist | - |
dc.contributor.author | Tor D Wager | - |
dc.date.available | 2017-09-05T05:28:00Z | - |
dc.date.created | 2017-03-21 | - |
dc.date.issued | 2017-03 | - |
dc.identifier.issn | 1097-6256 | - |
dc.identifier.uri | https://pr.ibs.re.kr/handle/8788114/3753 | - |
dc.description.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. | - |
dc.description.uri | 1 | - |
dc.language | 영어 | - |
dc.publisher | NATURE PUBLISHING GROUP | - |
dc.title | Building better biomarkers: Brain models in translational neuroimaging | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.identifier.wosid | 000394920400009 | - |
dc.identifier.scopusid | 2-s2.0-85013789441 | - |
dc.identifier.rimsid | 59032 | ko |
dc.date.tcdate | 2018-10-01 | - |
dc.contributor.affiliatedAuthor | Choong-Wan Woo | - |
dc.identifier.doi | 10.1038/nn.4478 | - |
dc.identifier.bibliographicCitation | NATURE NEUROSCIENCE, v.20, no.3, pp.365 - 377 | - |
dc.citation.title | NATURE NEUROSCIENCE | - |
dc.citation.volume | 20 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 365 | - |
dc.citation.endPage | 377 | - |
dc.date.scptcdate | 2018-10-01 | - |
dc.description.wostc | 46 | - |
dc.description.scptc | 52 | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | TREATMENT-RESISTANT DEPRESSION | - |
dc.subject.keywordPlus | HUMAN CEREBRAL-CORTEX | - |
dc.subject.keywordPlus | DIMENSIONAL PATTERN-CLASSIFICATION | - |
dc.subject.keywordPlus | INTRINSIC FUNCTIONAL CONNECTIVITY | - |
dc.subject.keywordPlus | PREDICTING TREATMENT RESPONSE | - |
dc.subject.keywordPlus | AUTISM SPECTRUM DISORDER | - |
dc.subject.keywordPlus | VENTRAL TEMPORAL CORTEX | - |
dc.subject.keywordPlus | SOCIAL ANXIETY DISORDER | - |
dc.subject.keywordPlus | PARKINSONS-DISEASE | - |
dc.subject.keywordPlus | ALZHEIMERS-DISEASE | - |