Evidence map›Paper›PMID 31852929›Full record

ArticleScientific reports2019

A Long Short-Term Memory neural network for the detection of epileptiform spikes and high frequency oscillations.

A V Medvedev, G I Agoureeva, A M Murro

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
6.2field-weighted citation impact, top 3% of its field
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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 68 citations in OpenAlex.

  1. Pooled it
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  13. AN ONLINE SPIKE DETECTION AND MONITORING FRAMEWORK IN IEEG RECORDED USING BRAIN INTERCHANGE DEVICE.Proceedings of the ... International Brain-Computer Interface Conference · 2024
    Article
  14. Review
  15. Article
  16. Networks through the lens of high-frequency oscillations.Frontiers in network physiology · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

A V MedvedevCenter for Functional and Molecular Imaging & Department of Neurology, Georgetown University, Washington, DC, USA. am236@georgetown.edu.
G I AgoureevaFaculty of Science and Engineering, Flinders University of South Australia (Retiree), Adelaide, SA, Australia.
A M MurroDepartment of Neurology, Medical College of Georgia, Augusta, GA, USA.
Augusta University · USFlinders University · AUGeorgetown University · US

Funding

Cross-frequency coupling: its role in brain function and dysfunctionRF1MH123192 · NIMH · GEORGETOWN UNIVERSITY · PI MEDVEDEV, ANDREI V · 2020 to 2020
$840k
NIMH NIH HHS RF1 MH123192
6 · The paper itself

Abstract

Over the last two decades, the evidence has been growing that in addition to epileptic spikes high frequency oscillations (HFOs) are important biomarkers of epileptogenic tissue. New methods of artificial intelligence such as deep learning neural networks can provide additional tools for automated analysis of EEG. Here we present a Long Short-Term Memory neural network for detection of spikes, ripples and ripples-on-spikes (RonS). We used intracranial EEG (iEEG) from two independent datasets. First dataset (7 patients) was used for network training and testing. The second dataset (5 patients) was used for cross-institutional validation. 1000 events of each class (spike, RonS, ripple and baseline) were selected from the candidates initially found using a novel threshold method. Network training was performed using random selections of 50-500 events (per class) from all patients from the 1

Indexed as

ElectrocorticographyAdolescentAdultBrainBrain WavesEpilepsyFemaleHumansMaleMiddle AgedNerve NetNeural Networks, ComputerSeizuresYoung Adult

Identifiers

PMID31852929
PMCPMC6920137
OpenAlexW2995047828

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.