Simon Fraser University

Published purpose

Artificial Intelligence (AI) is quickly penetrating healthcare, but the routine neurological assessment of patients at the primary point of care is still missing AI-enhanced neurologist-like approaches to deal with the complexity of all its data. Developing such AI tools is the focus of the Project, which seeks to address the primary question of whether a novel state-of-the-art machine learning approach, applied to routine clinical EEGs recorded in hospital, can support a more accurate diagnosis with higher efficiency for all categories of patients requiring neurological assessment at the primary point of care. The team will develop a prototype system to support experts in reviewing EEG data. The novel system will utilize state-of-the-art AI methods to identify key diagnostic and outcome-predictive features in the EEG data. The aim is to design AI systems to enhance workflow in data-intensive and time-sensitive settings.