Moving the field forward: detection of epileptiform abnormalities on scalp electroencephalography using deep learning - clinical application perspectives

M Janmohamed; D Nhu; L Kuhlmann; A Gilligan; CW Tan; P Perucca; TJ O'Brien; P Kwan

Journal article

Moving the field forward: detection of epileptiform abnormalities on scalp electroencephalography using deep learning - clinical application perspectives

M Janmohamed, D Nhu, L Kuhlmann, A Gilligan, CW Tan, P Perucca, TJ O'Brien, P Kwan

Brain Communications | OXFORD UNIV PRESS | Published : 2022

DOI: 10.1093/braincomms/fcac218

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Abstract

The application of deep learning approaches for the detection of interictal epileptiform discharges is a nascent field, with most studies published in the past 5 years. Although many recent models have been published demonstrating promising results, deficiencies in descriptions of data sets, unstandardized methods, variation in performance evaluation and lack of demonstrable generalizability have made it difficult for these algorithms to be compared and progress to clinical validity. A few recent publications have provided a detailed breakdown of data sets and relevant performance metrics to exemplify the potential of deep learning in epileptiform discharge detection. This review provides an..

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University of Melbourne Researchers

Levin Kuhlmann Author

Amanda Gilligan Author

Piero Perucca Author

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Grants

Awarded by Medical Research Future Fund Practitioner Fellowship

Awarded by National Health and Medical Research Council (NHMRC)

Awarded by National Health and Medical Research Council

Awarded by NHMRC

Funding Acknowledgements

M.J. receives support through an `Australian Government Research Training Program (RTP) Scholarship' for PhD at Monash University, Melbourne, Australia. P.K. is supported by the Medical Research Future Fund Practitioner Fellowship (MRF1136427). L.K. is supported by the National Health and Medical Research Council (NHMRC) (GNT1183119 and GNT1160815) and the Epilepsy Foundation of America. 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 and the Weary Dunlop Medical Research Foundation. T.J.O. is supported by an NHMRC Investigator Grant (APP1176426).