Literature DB >> 27940048

Automated spike detection in EEG.

W R S Webber1, Ronald P Lesser2.   

Abstract

Mesh：

Year:  2016        PMID： 27940048     DOI： 10.1016/j.clinph.2016.11.018

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN： 1388-2457            Impact factor:   3.708


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  6 in total

1.  Interictal epileptiform discharge characteristics underlying expert interrater agreement.

Authors:  Elham Bagheri; Justin Dauwels; Brian C Dean; Chad G Waters; M Brandon Westover; Jonathan J Halford
Journal:  Clin Neurophysiol       Date:  2017-07-18       Impact factor: 3.708

2.  A fast machine learning approach to facilitate the detection of interictal epileptiform discharges in the scalp electroencephalogram.

Authors:  Elham Bagheri; Jing Jin; Justin Dauwels; Sydney Cash; M Brandon Westover
Journal:  J Neurosci Methods       Date:  2019-07-13       Impact factor: 2.390

3.  CLASSIFIER CASCADE TO AID IN DETECTION OF EPILEPTIFORM TRANSIENTS IN INTERICTAL EEG.

Authors:  Elham Bagheri; Jing Jin; Justin Dauwels; Sydney Cash; M Brandon Westover
Journal:  Proc IEEE Int Conf Acoust Speech Signal Process       Date:  2018-09-13

4.  What it should mean for an algorithm to pass a statistical Turing test for detection of epileptiform discharges.

Authors:  M Brandon Westover; Jonathan J Halford; Matt T Bianchi
Journal:  Clin Neurophysiol       Date:  2017-03-16       Impact factor: 4.861

5.  A predictive epilepsy index based on probabilistic classification of interictal spike waveforms.

Authors:  Jesse A Pfammatter; Rachel A Bergstrom; Eli P Wallace; Rama K Maganti; Mathew V Jones
Journal:  PLoS One       Date:  2018-11-06       Impact factor: 3.240

6.  An automated, machine learning-based detection algorithm for spike-wave discharges (SWDs) in a mouse model of absence epilepsy.

Authors:  Jesse A Pfammatter; Rama K Maganti; Mathew V Jones
Journal:  Epilepsia Open       Date:  2019-02-06
  6 in total

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