Neural Information Processing

13th International Conference, ICONIP 2006, Hong Kong, China, October 3-6, 2006. Proceedings, Part III

Editors:

ISBN: 978-3-540-46484-6 (Print) 978-3-540-46485-3 (Online)

Table of contents (133 chapters)

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  1. Front Matter

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  2. Bioinformatics and Biomedical Applications

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      Pages 1-10

      DRFE: Dynamic Recursive Feature Elimination for Gene Identification Based on Random Forest

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      Pages 11-20

      Gene Feature Extraction Using T-Test Statistics and Kernel Partial Least Squares

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      Pages 21-29

      An Empirical Analysis of Under-Sampling Techniques to Balance a Protein Structural Class Dataset

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      Pages 30-39

      Prediction of Protein Interaction with Neural Network-Based Feature Association Rule Mining

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      Pages 40-47

      Prediction of Protein Secondary Structure Using Nonlinear Method

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      Pages 48-57

      Clustering Analysis for Bacillus Genus Using Fourier Transform and Self-Organizing Map

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      Pages 58-65

      Recurrence Quantification Analysis of EEG Predicts Responses to Incision During Anesthesia

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      Pages 66-73

      Wavelet Spectral Entropy for Indication of Epileptic Seizure in Extracranial EEG

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      Pages 74-81

      The Study of Classification of Motor Imaginaries Based on Kurtosis of EEG

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      Pages 82-91

      Automatic Detection of Critical Epochs in coma-EEG Using Independent Component Analysis and Higher Order Statistics

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      Pages 92-101

      Sparse Bump Sonification: A New Tool for Multichannel EEG Diagnosis of Mental Disorders; Application to the Detection of the Early Stage of Alzheimer’s Disease

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      Pages 102-109

      Effect of Diffusion Weighting and Number of Sensitizing Directions on Fiber Tracking in DTI

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      Pages 110-117

      3-D Reconstruction of Blood Vessels Skeleton Based on Neural Network

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      Pages 118-126

      Design of a Fuzzy Takagi-Sugeno Controller to Vary the Joint Knee Angle of Paraplegic Patients

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      Pages 127-136

      Characterization of Breast Abnormality Patterns in Digital Mammograms Using Auto-associator Neural Network

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      Pages 137-144

      Evolving Hierarchical RBF Neural Networks for Breast Cancer Detection

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      Pages 145-154

      Ovarian Cancer Prognosis by Hemostasis and Complementary Learning

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      Pages 155-164

      Multi-class Cancer Classification with OVR-Support Vector Machines Selected by Naïve Bayes Classifier

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      Pages 165-175

      Breast Cancer Diagnosis Using Neural-Based Linear Fusion Strategies

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      Pages 176-183

      A Quantitative Diagnostic Method Based on Bayesian Networks in Traditional Chinese Medicine

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