In hospital intensive care units, neurologists often use a simple scorecard to quickly evaluate a critically ill patient's likelihood of having a brain-damaging seizure so they can prevent it. The ...

Decoding the human brain using non-invasive methods is a significant challenge. This study aims to enhance electroencephalography (EEG) decoding by developing of machine learning methods. Specifically ...

Researchers at Duke University have developed an assistive machine learning model that greatly improves the ability of medical professionals to read the electroencephalography (EEG) charts of ...

It has been notably demonstrated in the Sequential Treatment Alternatives to Relieve Depression (STAR*D) study that antidepressants fail to facilitate remission in most patients with major depressive ...

Mayo Clinic scientists are using artificial intelligence (AI) and machine learning to analyze electroencephalogram (EEG) tests more quickly and precisely, enabling neurologists to find early signs of ...

Please provide your email address to receive an email when new articles are posted on . A wearable, portable electroencelphalogram, or EEG, system will allow clinicians to rapidly review real-time ...

Better understanding the brain’s response to electrical stimulation could open up new avenues for treating brain disorders. A device being development at the SLAC National Accelerator Laboratory and ...

Why Use EEG in the Critically Ill? Wilner: Thanks for joining us. I’m really glad we have this opportunity because this is a question that’s been bothering me about the application of resources. A ...

The first patenting from Encephalogix Inc. details its development of platform that uses machine learning and AI to analyze EEG data that is typically ignored.