An AI algorithm applied to POC EEG recordings can predict functional outcomes by measuring seizure burden. Higher seizure burden was associated with poorer functional outcomes in patients being monitored for seizures or at risk of seizures. An automated machine learning tool called Clarity can analyze seizure burden in real-time, providing valuable information on patient prognosis. The study suggests a shift towards integrating AI technology for automated EEG interpretation in managing critically ill patients with seizures. This innovative method shows promise in improving patient care and outcomes for those with neurological conditions, although more research is needed to confirm its effectiveness in clinical practice.
Source link
‘Compelling’ Results for AI EEG to Predict Outcomes
