Titlebook: Neural Information Processing; 13th International C Irwin King,Jun Wang,DeLiang Wang Conference proceedings 2006 Springer-Verlag Berlin Hei

使人入神

Automatic Detection of Critical Epochs in coma-EEG Using Independent Component Analysis and Higher Ogful dominant components from the EEG of patients in coma. A procedure for automatic critical epoch detection might support the doctor in the long time monitoring of the patients, this is why we are headed to find a procedure able to automatically quantify how much an epoch is critical or not. In th

昆蟲

Sparse Bump Sonification: A New Tool for Multichannel EEG Diagnosis of Mental Disorders; Applicationplications in early detection and diagnosis of early stage of Alzheimer’s disease. We propose here a novel approach based on multi channel sonification, with a time-frequency representation and sparsification process using bump modeling. The fundamental question explored in this paper is whether cli

抗原

Effect of Diffusion Weighting and Number of Sensitizing Directions on Fiber Tracking in DTI and accuracy of fiber tracking results depend on the quality of estimated DT which is determined by parameters of image acquisition protocol. The aim of this paper is to investigate what echo-planar image (EPI) acquisition parameters: the number of sensitizing directions K and diffusion weighting b

fidelity

凹槽

匍匐

Characterization of Breast Abnormality Patterns in Digital Mammograms Using Auto-associator Neural Ns type of breast abnormality patterns for benign and malignant class characterization using auto-associator neural network and original features. The characterized patterns are finally classified into benign and malignant classes using a classifier neural network. Grey-level based statistical featur

stressors

Evolving Hierarchical RBF Neural Networks for Breast Cancer Detectionl RBF network was employed to detect the breast cancel. For evolving a hierarchical RBF network model, Extended Compact Genetic Programming (ECGP), a tree-structure based evolutionary algorithm and the Differential Evolution (DE) are used to find an optimal detection model. The performance of propos

Vasoconstrictor

Ovarian Cancer Prognosis by Hemostasis and Complementary Learningnosis is required to determine the suitable therapeutic decision. Since abnormalities of hemostasis and increased risk of thrombosis are observed in cancer patient, assay involving hemostatic parameters can be potential prognosis tool. Thus a biological brain-inspired . (CLFNN) is proposed, to compl

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SOB