Connectomics in Neuroimaging by Archana Venkataraman
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Connectomics in Neuroimaging

Connectomics in Neuroimaging


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About the Book

Unsupervised Feature Selection via Adaptive Embedding and Sparse Learning for Parkinson's Disease Diagnosis.- A Novel Graph Neural Network to Localize Eloquent Cortex in Brain Tumor Patients from Resting-State fMRI Connectivity.- Graph Morphology-Based Genetic Algorithm for Classifying Late Dementia States.- Covariance Shrinkage for Dynamic Functional Connectivity.- Rapid Acceleration of the Permutation Test via Transpositions.- Heat kernels with functional connectomes reveal atypical energy transport in peripheral subnetworks in autism.- A Mass Multivariate Edge-wise Approach for Combining Multiple Connectomes to Improve the Detection of Group Differences.- Adversarial Connectome Embedding for Mild Cognitive Impairment Identification using Cortical Morphological Networks.- A Machine Learning Framework for Accurate Functional Connectome Fingerprinting and an Application of a Siamese Network.- Test-Retest Reliability of Functional Networks for Evaluation of Data-Driven Parcellation.- Constraining Disease Progression Models Using Subject Specific Connectivity Priors.- Hemodynamic Matrix Factorization for Functional Magnetic Resonance Imaging.- Network Dependency Index Stratified Subnetwork Analysis of Functional Connectomes: An application to autism.


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Product Details
  • ISBN-13: 9783030323905
  • Publisher: Springer International Publishing
  • Publisher Imprint: Springer
  • Height: 234 mm
  • No of Pages: 139
  • Spine Width: 8 mm
  • Weight: 272 gr
  • ISBN-10: 3030323900
  • Publisher Date: 18 Oct 2019
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Sub Title: Third International Workshop, Cni 2019, Held in Conjunction with Miccai 2019, Shenzhen, China, October 13, 2019, Proceedings
  • Width: 156 mm


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Connectomics in Neuroimaging
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