Designing weighted correlation kernels in convolutional neural networks for functional connectivity based brain disease diagnosis

Keyphrases

• Brain Regions 100%
• Functional Magnetic Resonance Imaging 100%
• Brain Disease Diagnosis 100%
• Functional Connectivity 100%
• Connectivity-based 100%
• Convolutional Neural Network 100%
• Weighted Correlation Coefficient 100%
• Correlation Kernel 100%
• Functional Networks 66%
• Dynamic Functional Connectivity 66%
• Pearson Correlation Coefficient Method 66%
• Temporal Features 33%
• High-level Features 33%
• Mild Cognitive Impairment 33%
• ADNI Dataset 33%
• Alzheimer's Disease 33%
• Kernel-based 33%
• Network Applications 33%
• Resting-state Functional Magnetic Resonance Imaging (rs-fMRI) 33%
• Network Features 33%
• Brain Networks 33%
• Disease Diagnosis 33%
• Clustering Coefficient 33%
• Weighting Factor 33%
• Global-local 33%
• Interaction Information 33%
• Global Brain 33%
• Brain Diseases 33%
• Specific Features 33%
• Network Construction 33%
• Diagnostic Model 33%
• Higher-order Networks 33%
• Network Measures 33%
• Neural Network Framework 33%
• Prodrome 33%
• Rich Interaction 33%
• Information in Networks 33%
• Observation Information 33%

Computer Science

• Functional Connectivity 100%
• Convolutional Neural Network 100%
• Pearson Correlation Coefficient 40%
• Experimental Result 20%
• Temporal Feature 20%
• Information Interaction 20%
• Clustering Coefficient 20%
• Functional State 20%