Nature

Flexible Patched Brain Transformer model for EEG decoding

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 ...
Nature

Development of a deep learning-based prediction model for postoperative delirium using intraoperative electroencephalogram in adults

Postoperative delirium (POD) is associated with increased morbidity and mortality. This study aims to develop a deep learning-based model (DELPHI-EEG) to predict postoperative delirium using ...
MobiHealthNews

EEG-based foundation AI for early brain disease diagnosis unveiled in India

An AI foundation model meant to "interpret and understand" the human brain using thousands of brain wave records has been introduced in India. Touted as a first of its kind in India, the brain ...
The American Journal of Managed Care

AI Model Interprets EEG Readings for Epilepsy With Human-Level Accuracy, Study Finds

A new artificial intelligence (AI) model may improve patient diagnosis and care among specialized epilepsy centers in underserved areas. The use of an artificial intelligence (AI) model to interpret ...
Business Wire

BrainScope’s EEG-Based Biomarker Predicts Dementia Risk Up to 7 Years Before Initial Diagnosis, Published in Nature Scientific Reports

ROCKVILLE, Md.--(BUSINESS WIRE)--BrainScope, a commercial-stage medical neurotechnology company applying artificial intelligence and computational neuroscience to brain electrical activity (EEG), ...