Exploring temporal information in neonatal seizures using a dynamic time warping based SVM kernel-Reference-Cited by-同舟云学术

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Exploring temporal information in neonatal seizures using a dynamic time warping based SVM kernel

Published:2017-03 Issue: Volume:82 Page:100-110
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Ahmed Rehan,Temko Andriy,Marnane William P.,Boylan Geraldine,Lightbody Gordon

Funder

Science Foundation Ireland Principal Investigator Award

Science Foundation Ireland Centres Programme Award

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference49 articles.

1. A population-based study of neonatal seizures in Fayette County, Kentucky;Lanska;Neurology,1995

2. Significance of seizures in very low-birthweight infants;Watkins;Dev. Med. Child Neurol.,1988

3. Clinical types and possible etiologies of neonatal seizures: a hospital based study;AL-Naddawi;J. Fac. Med. Baghdad,2011

4. The temporal evolution of electrographic seizure burden in neonatal hypoxic ischemic encephalopathy;Lynch;Epilepsia,2012

5. Non-expert use of the cerebral function monitor for neonatal seizure detection;Rennie;Arch. Dis. Child. – Fetal Neonatal Ed.,2004

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1. The past, current, and future of neonatal intensive care units with artificial intelligence: a systematic review;npj Digital Medicine;2023-11-27

2. Automatic Epileptic Seizure Detection Using PSO-Based Feature Selection and Multilevel Spectral Analysis for EEG Signals;Journal of Sensors;2022-10-28

3. Modified Time-Frequency Marginal Features for Detection of Seizures in Newborns;Sensors;2022-04-15

4. Texture analysis based graph approach for automatic detection of neonatal seizure from multi-channel EEG signals;Measurement;2022-02

5. Geographical discrimination of propolis using dynamic time warping kernel principal components analysis;Expert Systems with Applications;2022-01

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