Differentiating Ischemic Stroke Patients from Healthy Subjects Using a Large-Scale, Retrospective EEG Database and Machine Learning Methods

We set out to develop a machine learning model capable of distinguishing patients presenting with ischemic stroke from a healthy cohort of subjects. The model relies on a 3-minute resting electroencephalogram (EEG) recording from which features can be computed.

Source: Journal of Stroke and Cerebrovascular Diseases - April 15, 2024 Category: Neurology Authors: William Peterson, Nithya Ramakrishnan, Krag Browder, Nerses Sanossian, Peggy Nguyen, Ezekiel Fink Source Type: research