Accurate identification of EEG recordings with interictal epileptiform discharges using a hybrid approach: Artificial intelligence supervised by human experts-Reference-Cited by-同舟云学术

Accurate identification of EEG recordings with interictal epileptiform discharges using a hybrid approach: Artificial intelligence supervised by human experts

Published:2022-03-07 Issue:5 Volume:63 Page:1064-1073
ISSN:0013-9580
Container-title:Epilepsia
language:en
Short-container-title:Epilepsia

Author:

Kural Mustafa Aykut¹²³,Jing Jin⁴^ORCID,Fürbass Franz⁵^ORCID,Perko Hannes⁵,Qerama Erisela²³,Johnsen Birger²³,Fuchs Steffen²,Westover M. Brandon⁴,Beniczky Sándor¹²³^ORCID

Affiliation:

1. Department of Clinical Neurophysiology Danish Epilepsy Centre Filadelfia Dianalund Denmark

2. Department of Clinical Neurophysiology Aarhus University Hospital Aarhus Denmark

3. Department of Clinical Medicine Aarhus University Aarhus Denmark

4. Department of Neurology Harvard Medical School Massachusetts General Hospital Boston Massachusetts USA

5. Center for Health & Bioresources AIT Austrian Institute of Technology GmbH Vienna Austria

Funder

Foundation for the National Institutes of Health

Publisher

Wiley

Subject

Neurology (clinical),Neurology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/epi.17206

Reference43 articles.

1. Clinical utility of EEG in diagnosing and monitoring epilepsy in adults

2. Interictal EEG and the Diagnosis of Epilepsy

3. Machine learning for detection of interictal epileptiform discharges

4. Machine learning and wearable devices of the future;Beniczky S;Epilepsia,2021

5. Fast evaluation of interictal spikes in long-term EEG by hyper-clustering

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