Evaluating Models of Dynamic Functional Connectivity Using Predictive Classification Accuracy

Keyphrases

• Classification Accuracy 100%
• Evaluation Model 100%
• Dynamic Model 100%
• Dynamic Functional Connectivity 100%
• Predictive Classification 100%
• Emission Model 66%
• Statistical Dependence 66%
• Healthy Controls 33%
• Functional Magnetic Resonance Imaging 33%
• Schizophrenic Patients 33%
• Patient-controlled 33%
• Dynamic Change 33%
• Brain State 33%
• Resting-state Functional Magnetic Resonance Imaging (rs-fMRI) 33%
• Classification Results 33%
• Parametrization 33%
• Full Covariance Matrix 33%
• Hidden Markov Model 33%
• Group Independent Component Analysis 33%
• Dynamic Features 33%

Computer Science

• Classification Accuracy 100%
• Functional Connectivity 100%
• Covariance Matrix 33%
• Healthy Control 33%
• classification result 33%
• Functional State 33%
• Independent Component Analysis 33%
• Schizophrenic Patient 33%
• Parametrization 33%

Neuroscience

• Dynamic Functional Connectivity 100%
• Functional Magnetic Resonance Imaging 33%
• Independent Component Analysis 33%
• Hidden Markov Model 33%