AIMC Topic: Consciousness Disorders
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Disentangling disorders of consciousness: Insights from diffusion tensor imaging and machine learning.
Human brain mapping
Sep 13, 2016
Previous studies have suggested that disorders of consciousness (DOC) after severe brain injury may result from disconnections of the thalamo-cortical system. However, thalamo-cortical connectivity differences between vegetative state (VS), minimally...
"Look at my classifier's result": Disentangling unresponsive from (minimally) conscious patients.
NeuroImage
Dec 12, 2015
Given the fact that clinical bedside examinations can have a high rate of misdiagnosis, machine learning techniques based on neuroimaging and electrophysiological measurements are increasingly being considered for comatose patients and patients with ...
Toward a Universal Map of EEG: A Semantic, Low-Dimensional Manifold for EEG Classification, Clustering, and Prognostication.
Annals of neurology
Aug 1, 2025
OBJECTIVE: Prognostication in patients with disorders of consciousness (DOCs) remains challenging because of heterogeneous etiologies, pathophysiologies and, consequently, highly variable electroencephalograms (EEGs). Here, we use EEG patterns that a...
Is Robotic Gait Training Feasible in Adults With Disorders of Consciousness?
The Journal of head trauma rehabilitation
Jan 1, 2020
OBJECTIVE: To investigate the feasibility and safety of robotic-assisted gait training (RAGT) in adults with disorders of consciousness (DoC).
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