36 citations · 36 across the 2 of their papers we have counts for
2 papers
eess.SP2025
Machine-learning competition to grade EEG background patterns in newborns with hypoxic-ischaemic encephalopathy
Fabio Magarelli, Geraldine B. Boylan, Saeed Montazeri +5
Machine learning (ML) has the potential to support and improve expert performance in monitoring the brain function of at-risk newborns. Developing accurate and reliable ML models d…
physics.med-ph2022★ 36 cited
Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy
John M O'Toole, Sean R Mathieson, Sumit A Raurale +4
This report describes a set of neonatal electroencephalogram (EEG) recordings graded according to the severity of abnormalities in the background pattern. The dataset consists of 1…