Aim Artificial intelligence (AI) and machine learning (ML) are important areas of computer
science that have recently attracted attention for their application to medicine. However, as …

Advances over the past two decades in functional neuroimaging have provided new
diagnostic and prognostic tools for patients with severe brain injury. Some of the most …

The utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving the way for
significant strides in patient diagnosis, treatment, and prognostication in neurocritical care …

Auditory processing and the complexity of neural activity can both indicate residual
consciousness levels and differentiate states of arousal. However, how measures of neural …

Electroencephalography (EEG) is invaluable in the management of acute neurological
emergencies. Characteristic EEG changes have been identified in diverse neurologic …

Aim Assess the prognostic ability of a non-highly malignant and reactive EEG to predict
good outcome after cardiac arrest (CA). Methods Prospective observational multicentre …

Outcome prognostication in comatose patients after cardiac arrest (CA) remains to date a
challenge. The major determinant of clinical outcome is the post-hypoxic/ischemic …

Determining the level of consciousness in patients with brain injury—and more
fundamentally, establishing what they can experience—is ethically and clinically impactful …

Recent advances in clinical electroencephalography : Current Opinion in Neurology Recent
advances in clinical electroencephalography : Current Opinion in Neurology Log in or Register …

Aim of the review The primary aim of this systematic review was to investigate the most
common electroencephalogram (EEG)-based machine learning (ML) model with the highest …