A High Accuracy Electrographic Seizure Classifier Trained Using Semi-Supervised Labeling Applied to a Large Spectrogram Dataset

A High Accuracy Electrographic Seizure Classifier Trained Using Semi-Supervised Labeling Applied to a Large Spectrogram Dataset

The objective of this study was to explore using ECoG spectrogram images for training reliable cross-patient electrographic seizure classifiers, and to characterize the classifiers’ test accuracy as a function of amount of training data. ECoG channels in ∼138,000 time-series ECoG records from 113 pa...

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Bibliographic Details
Main Authors: Wade Barry, Sharanya Arcot Desai, Thomas K. Tcheng, Martha J. Morrell
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Neuroscience
Subjects:
semi-supervised labeling
ECoG labeling
big data
electrographic seizure classifier
epilepsy
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2021.667373/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2021.667373/full

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