ArticleScientific data2023
Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 28 citations in OpenAlex.
- Assessing Early Severity of Hypoxic-Ischemic Encephalopathy: The Role of Electroencephalogram Background in Addition to Sarnat Exam.The Journal of pediatrics · 2025Trial
- High-throughput analysis of multimodal monitoring data: the role of machine learning in early warning systems for high-risk neonates.BMJ paediatrics open · 2026Review
- Acupressure Potentially Promoting the Learning and Memory Capabilities of Hypoxic Ischemic Cerebral Palsy Rats.Neural plasticity · 2026Article
- Article
- Short-horizon neonatal seizure prediction using EEG-based deep learning.PLOS digital health · 2025Article
- Long-Term Neonatal EEG Modeling with DSP and ML for Grading Hypoxic-Ischemic Encephalopathy Injury.Sensors (Basel, Switzerland) · 2025Article
- Machine learning for forecasting initial seizure onset in neonatal hypoxic-ischemic encephalopathy.Epilepsia · 2025Article
- Co-developing sleep-wake and sensory foundations for cognition in the human fetus and newborn.Developmental cognitive neuroscience · 2025Review
- Effective classification for neonatal brain injury using EEG feature selection based on elastic net regression and improved crow search algorithm.PeerJ. Computer science · 2025Article
- A finer-grained high altitude EEG dataset for hypoxia levels assessment.Scientific data · 2024Article
- Analysis of the impact of deep learning know-how and data in modelling neonatal EEG.Scientific reports · 2024Article
- Prognostic value of quantitative EEG in early hours of life for neonatal encephalopathy and neurodevelopmental outcomes.Pediatric research · 2024Article
- Quantitative Electroencephalography in Term Neonates During the Early Postnatal Period Across Various Sleep States.Nature and science of sleep · 2024Article
- Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy.Scientific data · 2023Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
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Abstract
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 169 hours of multichannel EEG from 53 neonates recorded in a neonatal intensive care unit. All neonates received a diagnosis of hypoxic-ischaemic encephalopathy (HIE), the most common cause of brain injury in full term infants. For each neonate, multiple 1-hour epochs of good quality EEG were selected and then graded for background abnormalities. The grading system assesses EEG attributes such as amplitude, continuity, sleep-wake cycling, symmetry and synchrony, and abnormal waveforms. Background severity was then categorised into 4 grades: normal or mildly abnormal EEG, moderately abnormal EEG, majorly abnormal EEG, and inactive EEG. The data can be used as a reference set of multi-channel EEG for neonates with HIE, for EEG training purposes, or for developing and evaluating automated grading algorithms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.