DOI: 10.25881/BPNMSC.2020.35.43.014

Authors

Karpov O.E.1, Penzin O.V.1, Panin I.I.2, 3, Utyashev N.P.1

1 Pirogov National Medical and Surgical Center, Moscow

2 SberMedAI LLC., Moscow

3 Kharkevich Institute for Information Transmission Problems, Moscow

Abstract

The paper considers an algorithm for detecting focal epileptiform discharges, created using convolutional neural networks.

A negative predictive value, NPV, tending to 100% (97.4–99.7% with a prevalence of 0.1–5%) provides a high likelihood that the site marked by the algorithm as normal does not actually contain epileptiform discharges.

Thus, the algorithm satisfies the initial requirement to search for regions of interest for detailed analysis by a medical specialist.

Keywords: epilepsy, focal discharges, EEG, machine learning, convolutional neural networks.

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For citation

Karpov O.E., Penzin O.V., Panin I.I., Utyashev N.P. Analysis of EEG signals using machine learning technologies for detecting focal epileptiform discharges. Bulletin of Pirogov National Medical & Surgical Center. 2020;4(15):69-73. (In Russ.) https://doi.org/10.25881/BPNMSC.2020.35.43.014