Titlebook: Brain Informatics and Health; 8th International Co Yike Guo,Karl Friston,Hanchuan Peng Conference proceedings 2015 Springer International P

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Two-Dimensional Enrichment Analysis for Mining High-Level Imaging Genetic Associationsamined for significant associations with a phenotype to help increase statistical power and improve biological interpretation. In this work, we expand the scope of enrichment analysis into brain imaging genetics, an emerging field that studies how genetic variation influences brain structure and fun

GROVE

Minimum Partial Correlation: An Accurate and Parameter-Free Measure of Functional Connectivity in fMsing approach to generate hypotheses and features for prediction. The most widely used method for inferring functional connectivity is full correlation, but it cannot differentiate direct and indirect effects. This disadvantage is often avoided by fully partial correlation, but this method suffers f

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A Model-Guided String-Based Approach to White Matter Fiber-Bundles Extractiones generated by tractography algorithms. Our approach is based on: . an approximate shape model of certain fiber-bundles constructed by an expert operator; . a particular string representation of fibers; . a new string similarity metric. It transforms the fiber-bundles of both the model and the trac

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Towards the Identification of Disease Signaturesading to a new systematic understanding of their causes, and new diagnostic tools. In this paper we present the challenges and steps taken towards the identification of disease signatures, through the Medical Informatics Platform of the Human Brain Project, that will expedite diagnosis and lead to m

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The Unsupervised Hierarchical Convolutional Sparse Auto-Encoder for Neuroimaging Data Classificationd small sample size characteristics pose many challenges to neuroimaging classification. The traditional neuroimaging classification solutions are tensor-based models, which may not fully consider the structural information and can’t mine the essential features of the input data. Considering the com

BAIL

A Personalized Method of Literature Recommendation Based on Brain Informatics Provenances kind of important knowledge source. However, it is difficult for researchers to find really useful references from a large number of literatures. This paper proposes a personalized method of literature recommendation based on BI provenances. By adopting the interest retention model, user models can