Evidence map›Paper›PMID 39107521›Full record

ArticlePediatric research2024

Free access via computational cloud to deep learning-based EEG assessment in neonatal hypoxic-ischemic encephalopathy: revolutionary opportunities to overcome health disparities.

Robertino Dilena, Maria Roberta Cilio

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PubMed Publisher
In one paragraph

Article in Pediatric research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Robertino DilenaClinical Neurophysiology Unit, Department of Neuroscience, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Maria Roberta CilioDivision of Pediatric Neurology, Department of Pediatrics, Saint-Luc University Hospital, and Institute of Neuroscience, Catholic University of Louvain, Brussels, Belgium. roberta.cilio@uclouvain.be.ORCID 0000-0003-2481-8053

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Deep LearningElectroencephalographyHypoxia-Ischemia, BrainBrainHealthcare DisparitiesHumansInfant, Newborn

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.