Functional connectivity based machine learning approach for autism detection in young children using MEG signals

Keyphrases

• Young children 100%
• Functional Connectivity 100%
• Machine Learning Approach 100%
• Connectivity-based 100%
• Autism Detection 100%
• MEG Signals 100%
• Classification Performance 66%
• Delta Band 66%
• Artificial Neural Network 66%
• Childhood Autism 66%
• Autism Spectrum Disorder 66%
• Support Vector Machine Classifier 66%
• Brain Connectivity Analysis 66%
• G-band 66%
• Typically Developing children 66%
• Connectivity Pattern 66%
• Connectivity Analysis 66%
• Functional Brain Connectivity 66%
• Classification Accuracy 33%
• High Performance 33%
• Brain Regions 33%
• Brain Oscillations 33%
• Statistical Analysis 33%
• Neural Systems 33%
• Resting State 33%
• Autism 33%
• Network Connectivity 33%
• Neural Activity 33%
• High Classification Accuracy 33%
• Brain Response 33%
• Machine Learning Framework 33%
• Autism Spectrum Disorder children 33%
• Life Outcomes 33%
• Neurodevelopmental Disorders 33%
• Hyperconnectivity 33%
• Magnetoencephalogram 33%
• High-gamma 33%
• Connectivity Features 33%
• Autism Biomarkers 33%
• Autism Symptomatology 33%

Neuroscience

• Functional Connectivity 100%
• Autism 100%
• Magnetoencephalography 100%
• Pervasive Developmental Disorder 83%
• Artificial Neural Network 33%
• Support Vector Machine 33%
• Neural System 16%
• Neural Oscillation 16%
• Neurodevelopmental Disorder 16%
• Brain Region 16%