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Free Access Via Computational Cloud to Deep Learning-based EEG Assessment in Neonatal Hypoxic-ischemic Encephalopathy: Revolutionary Opportunities to Overcome Health Disparities

Overview
Journal Pediatr Res
Specialties Biology
Pediatrics
Date 2024 Aug 6
PMID 39107521
Authors
Robertino Dilena
Maria Roberta Cilio
Affiliations
Soon will be listed here.
Abstract

In this issue of Pediatric Research, Kota et al. evaluate a novel monitoring visual trend using deep-learning - Brain State of the Newborn (BSN)- based EEG as a bedside marker for severity of the encephalopathy in 46 neonates with hypoxic-ischemic encephalopathy (HIE) compared with healthy infants. Early BSN distinguished between normal and abnormal outcome, and correlated with the Total Sarnat Score.

Citing Articles

Automated assessment of EEG background for neurodevelopmental prediction in neonatal encephalopathy.

Lagace M, Montazeri S, Kamino D, Mamak E, Ly L, Hahn C Ann Clin Transl Neurol. 2024; 11(12):3267-3279.

PMID: 39543820 PMC: 11651191. DOI: 10.1002/acn3.52233.

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