Prediction of brain maturity in infants using machine-learning algorithms

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical...

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Vydáno v:	NeuroImage (Orlando, Fla.) Ročník 136; s. 1 - 9
Hlavní autoři:	Smyser, Christopher D., Dosenbach, Nico U.F., Smyser, Tara A., Snyder, Abraham Z., Rogers, Cynthia E., Inder, Terrie E., Schlaggar, Bradley L., Neil, Jeffrey J.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Elsevier Inc 01.08.2016 Elsevier Limited
Témata:	Age Algorithms Alzheimer's disease Brain - anatomy & histology Brain - growth & development Brain Mapping - methods Brain research Classification Developmental neuroimaging Female Functional MRI Gestational Age Hospitals Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Infant Infant, Newborn Infant, Premature - growth & development Magnetic Resonance Imaging - methods Male Medical imaging Methods Multivariate pattern analysis Pattern Recognition, Automated - methods Pediatrics Prematurity Prognosis Regression Analysis Reproducibility of Results Sensitivity and Specificity Studies Support Vector Machine Multivariate pattern analysis Developmental neuroimaging PMA rs-fMRI NICU MNI Infant SVM LOOCV RSN ROI SVR Prematurity GA BOLD Functional MRI MVPA EPI
ISSN:	1053-8119, 1095-9572
On-line přístup:	Získat plný text
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