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Dynamic Bayesian network modeling of fMRI: A comparison of group-analysis methods
Bayesian network (BN) modeling has recently been introduced as a tool for determining the dependencies between brain regions from functional-magnetic-resonance-imaging (fMRI) data. However, studiesExpand
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Controlling the False Discovery Rate of the Association/Causality Structure Learned with the PC Algorithm
  • J. Li, Z. Wang
  • Computer Science, Mathematics
  • J. Mach. Learn. Res.
  • 1 December 2009
In real world applications, graphical statistical models are not only a tool for operations such as classification or prediction, but usually the network structures of the models themselves are alsoExpand
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Development of the human fetal hippocampal formation during early second trimester
Development of the fetal hippocampal formation has been difficult to fully describe because of rapid changes in its shape during the fetal period. The aims of this study were to: (1) segment theExpand
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Effects of drip irrigation system uniformity and nitrogen applied on deep percolation and nitrate leaching during growing seasons of spring maize in semi-humid region
Drip system uniformity is one of the important factors affecting the deep percolation and nitrate leaching under drip-irrigated crops. Field experiments were conducted during two growing seasons ofExpand
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Spatial–temporal atlas of human fetal brain development during the early second trimester
During the second trimester, the human fetal brain undergoes numerous changes that lead to substantial variation in the neonatal in terms of its morphology and tissue types. As fetal MRI is more andExpand
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Kid-Net: Convolution Networks for Kidney Vessels Segmentation from CT-Volumes
Semantic image segmentation plays an important role in modeling patient-specific anatomy. We propose a convolution neural network, called Kid-Net, along with a training schema to segment kidneyExpand
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Dynamic Bayesian networks (DBNS) demonstrate impaired brain connectivity during performance of simultaneous movements in Parkinson's disease
Many symptoms of brain diseases may be caused by altered connectivity between brain regions, necessitating the development of suitable models for inferring effective connectivity in fMRI. Inspired byExpand
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Local Linear Discriminant Analysis (LLDA) for group and region of interest (ROI)-based fMRI analysis
A post-processing method for group discriminant analysis of fMRI is proposed. It assumes that the fMRI data have been pre-processed and analyzed so that each voxel is given a statistic specifyingExpand
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Bayesian Network Modeling for Discovering “Dependent Synergies” Among Muscles in Reaching Movements
The coordinated activities of muscles during reaching movements can be characterized by appropriate analysis of simultaneously-recorded surface electromyograms (sEMGs). Many recent sEMG studies haveExpand
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Learning brain connectivity with the false-discovery-rate-controlled PC-algorithm
  • J. Li, Z. Wang, M. McKeown
  • Medicine, Computer Science
  • 30th Annual International Conference of the IEEE…
  • 14 October 2008
Discovering the connectivity networks in the brain, i.e. the neural influence that brain regions exert over one another, has attracted increasing research attention in studies on brain functions. AnExpand
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