Deep active learning for interictal ictal injury continuum EEG patterns

OBJECTIVES: Seizures and seizure-like electroencephalography (EEG) patterns, collectively referred to as “ictal interictal injury continuum” (IIIC) patterns, are commonly encountered in critically ill patients. Automated detection is important for patient care and to enable research. However, traini...

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書誌詳細
出版年:J Neurosci Methods
主要な著者: Ge, Wendong, Jing, Jin, An, Sungtae, Herlopian, Aline, Ng, Marcus, Struck, Aaron F., Appavu, Brian, Johnson, Emily L., Osman, Gamaleldin, Haider, Hiba A., Karakis, Ioannis, Kim, Jennifer A., Halford, Jonathan J., Dhakar, Monica B., Sarkis, Rani A., Swisher, Christa B., Schmitt, Sarah, Lee, Jong Woo, Tabaeizadeh, Mohammad, Rodriguez, Andres, Gaspard, Nicolas, Gilmore, Emily, Herman, Susan T., Kaplan, Peter W., Pathmanathan, Jay, Hong, Shenda, Rosenthal, Eric S., Zafar, Sahar, Sun, Jimeng, Westover, M. Brandon
フォーマット: Artigo
言語:Inglês
出版事項: 2020
主題:
Article
オンライン･アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC8135050/
https://ncbi.nlm.nih.gov/pubmed/33131680
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jneumeth.2020.108966
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