Deep learning for automated epileptiform discharge detection from scalp EEG: A systematic review

D Nhu; M Janmohamed; A Antonic-Baker; P Perucca; TJ O’Brien; AK Gilligan; P Kwan; CW Tan; L Kuhlmann

Journal article

Deep learning for automated epileptiform discharge detection from scalp EEG: A systematic review

D Nhu, M Janmohamed, A Antonic-Baker, P Perucca, TJ O’Brien, AK Gilligan, P Kwan, CW Tan, L Kuhlmann

Journal of Neural Engineering | Published : 2022

DOI: 10.1088/1741-2552/ac9644

Abstract

Automated interictal epileptiform discharge (IED) detection has been widely studied, with machine learning methods at the forefront in recent years. As computational resources become more accessible, researchers have applied deep learning (DL) to IED detection with promising results. This systematic review aims to provide an overview of the current DL approaches to automated IED detection from scalp electroencephalography (EEG) and establish recommendations for the clinical research community. We conduct a systematic review according to the PRISMA guidelines. We searched for studies published between 2012 and 2022 implementing DL for automating IED detection from scalp EEG in major medical a..

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University of Melbourne Researchers

Piero Perucca Author

Amanda Gilligan Author

Patrick Kwan Author

Levin Kuhlmann Author

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Grants

Awarded by Epilepsy Foundation

Funding Acknowledgements

D N is supported by the Graduate Research Industry Scholarship (GRIP) at Monash University, Australia. P P is supported by the National Health and Medical Research Council (APP1163708), the Epilepsy Foundation, The University of Melbourne, Monash University, Brain Australia, Norman Beischer Medical Research Foundation, and the Weary Dunlop Medical Research Foundation. P K is supported by a Medical Research Future Fund Practitioner Fellowship (MRF1136427). M J is supported by the Monash RTP Stipend Scholarship. L K is supported by the National Health and Medical Research Council (GNT1183119 and GNT1160815) and the Epilepsy Foundation of America.