Multivariate decoding of cerebral blood flow measures in a clinical model of on-going postsurgical pain

Recent reports of multivariate machine learning (ML) techniques have highlighted their potential use to detect prognostic and diagnostic markers of pain. However, applications to date have focussed on acute experimental nociceptive stimuli rather than clinically relevant pain states. These reports h...

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Bibliographic Details
Published in:	Human brain mapping Vol. 36; no. 2; pp. 633 - 642
Main Authors:	O'Muircheartaigh, Jonathan, Marquand, Andre, Hodkinson, Duncan J., Krause, Kristina, Khawaja, Nadine, Renton, Tara F., Huggins, John P., Vennart, William, Williams, Steven C.R., Howard, Matthew A.
Format:	Journal Article
Language:	English
Published:	United States Blackwell Publishing Ltd 01.02.2015 John Wiley & Sons, Inc John Wiley and Sons Inc
Subjects:	Adult arterial spin labeling Artificial Intelligence biomarker Cerebrovascular Circulation - physiology Discriminant Analysis Feasibility Studies Humans machine learning Magnetic Resonance Imaging - methods Male Molar, Third - surgery Multivariate Analysis Normal Distribution pain Pain Measurement Pain, Postoperative - diagnosis Pain, Postoperative - physiopathology Sensitivity and Specificity Tooth Extraction - adverse effects Young Adult pain biomarker machine learning arterial spin labeling
ISSN:	1065-9471, 1097-0193, 1097-0193
Online Access:	Get full text
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