Dataset for the accepted publication: "Accuracy of EEG Biomarkers in the Detection of Clinical Outcome in Disorders of Consciousness after Severe Acquired Brain Injury: Preliminary Results of a Pilot Study Using a Machine Learning Approach
International audienceScientific advances in electrophysiology and clinical neuroscience have highli...
Different neuroimaging techniques can monitor the brain activity. Electroencephalogram (EEG) is the ...
Objective: To investigate the diagnostic utility of electrophysiological recordings during active co...
Accurate outcome detection in neuro-rehabilitative settings is crucial for appropriate long-term reh...
Traumatic Brain Injury (TBI) is a highly prevalent and serious public health concern. TBI is defined...
Objective: Electroencephalogram (EEG) reactivity is a robust predictor of neurological recovery afte...
Mild Traumatic Brain Injuries (mTBI) are very common and can have a significant impact on an individ...
Abstract Background The reliable diagnosis of a mild traumatic brain injury (mTBI) is a pervasive pr...
In recent years advanced neurocomputing and machine learning techniques have been used successfully ...
With the fast improvement of neuroimaging data acquisition strategies, there has been a significant ...
Objective: To test whether 1) quantitative analysis of EEG reactivity (EEG-R) using machine learning...
Disorders of consciousness (DoC) happen frequently in various brain injuries. Their detection helps ...
In recent years advanced neurocomputing and machine learning techniques have been used successfully ...
Contains fulltext : 176863.pdf (publisher's version ) (Open Access)For some patien...
Due to the difficulties and complications in the quantitative assessment of traumatic brain injury (...
International audienceScientific advances in electrophysiology and clinical neuroscience have highli...
Different neuroimaging techniques can monitor the brain activity. Electroencephalogram (EEG) is the ...
Objective: To investigate the diagnostic utility of electrophysiological recordings during active co...
Accurate outcome detection in neuro-rehabilitative settings is crucial for appropriate long-term reh...
Traumatic Brain Injury (TBI) is a highly prevalent and serious public health concern. TBI is defined...
Objective: Electroencephalogram (EEG) reactivity is a robust predictor of neurological recovery afte...
Mild Traumatic Brain Injuries (mTBI) are very common and can have a significant impact on an individ...
Abstract Background The reliable diagnosis of a mild traumatic brain injury (mTBI) is a pervasive pr...
In recent years advanced neurocomputing and machine learning techniques have been used successfully ...
With the fast improvement of neuroimaging data acquisition strategies, there has been a significant ...
Objective: To test whether 1) quantitative analysis of EEG reactivity (EEG-R) using machine learning...
Disorders of consciousness (DoC) happen frequently in various brain injuries. Their detection helps ...
In recent years advanced neurocomputing and machine learning techniques have been used successfully ...
Contains fulltext : 176863.pdf (publisher's version ) (Open Access)For some patien...
Due to the difficulties and complications in the quantitative assessment of traumatic brain injury (...
International audienceScientific advances in electrophysiology and clinical neuroscience have highli...
Different neuroimaging techniques can monitor the brain activity. Electroencephalogram (EEG) is the ...
Objective: To investigate the diagnostic utility of electrophysiological recordings during active co...