Semi-supervised training data selection improves seizure forecasting in canines with epilepsy-Reference-Cited by-同舟云学术

Semi-supervised training data selection improves seizure forecasting in canines with epilepsy

Published:2020-03 Issue: Volume:57 Page:101743
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Nasseri Mona^ORCID,Kremen Vaclav,Nejedly Petr,Kim Inyong,Chang Su-Youne,Jo Hang Joon,Guragain Hari^ORCID,Nelson Nathaniel,Patterson Edward,Sturges Beverly K.,Crowe Chelsea M.^ORCID,Denison Tim,Brinkmann Benjamin H.^ORCID,Worrell Gregory A.

Funder

Mayo Clinic

National Institutes of Health

Epilepsy Foundation

Czech Technical University in Prague

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference28 articles.

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2. Crowdsourcing reproducible seizure forecasting in human and canine epilepsy;Brinkmann;Brain,2016

3. Views of patients with epilepsy on seizure prediction devices;Schulze-Bonhage;Epilepsy Behav.,2010

4. Seizure prediction and documentation—two important problems;Elger;Lancet Neurol.,2013

5. Prediction of seizure likelihood with a long-term, implanted seizure advisory system in patients with drug-resistant epilepsy: a first-in-man study;Cook;Lancet Neurol.,2013

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