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

Autor: Mustafa Aykut Kural, Jin Jing, Franz Fürbass, Hannes Perko, Erisela Qerama, Birger Johnsen, Steffen Fuchs, M. Brandon Westover, Sándor Beniczky

Publikováno v: Kural, M A, Jing, J, Fürbass, F, Perko, H, Qerama, E, Johnsen, B, Fuchs, S, Westover, M B & Beniczky, S 2022, ' Accurate identification of EEG recordings with interictal epileptiform discharges using a hybrid approach : Artificial intelligence supervised by human experts ', Epilepsia, vol. 63, no. 5, pp. 1064-1073 . https://doi.org/10.1111/epi.17206

Objective: To evaluate the diagnostic performance of artificial intelligence (AI)–based algorithms for identifying the presence of interictal epileptiform discharges (IEDs) in routine (20-min) electroencephalography (EEG) recordings. Methods: We ev

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::355cc5a72b509dd513fb746f429bdd68
https://pure.au.dk/portal/da/publications/accurate-identification-of-eeg-recordings-with-interictal-epileptiform-discharges-using-a-hybrid-approach(48f0a1ae-faab-4e47-8df2-c7016ffd1a8a).html

Deep learning for estimation of functional brain maturation from EEG of premature neonates

Autor: Laura Gschwandtner, Tobias Werther, Franz Fürbass, Hannes Perko, Lisa Oberdorfer, Vito Giordano, Tilmann Kluge, Nathan J. Stevenson, M. Hartmann, Angelika Berger, Katrin Klebermas-Schrehof, G. Gritsch

Publikováno v: EMBC

EEG monitoring of early brain function and development in neonatal intensive care units may help to identify infants with high risk of serious neurological impairment and to assess brain maturation for evaluation of neurodevelopmental progress. Autom

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::856e5c9ed46f9c7c8d3522467048fdb8
https://pubmed.ncbi.nlm.nih.gov/33017941

A Comparison of Rule-Based and Machine Learning Methods for Classification of Spikes in EEG

Autor: Tilmann Kluge, A.M. Skupch, Franz Fürbass, G. Gritsch, Hannes Perko, M. Hartmann, Wolfgang Ganglberger

Publikováno v: Journal of Communications. :589-595

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1b9f7e8f9b669521d16ffe9dec5548cb
https://doi.org/10.12720/jcm.12.10.589-595

High density wireless EEG prototype: Design and evaluation against reference equipment

Autor: Marco Passoni, Stefano Rossi, Pauly P. W. Ossenblok, Hannes Perko, Refet Firat Yazicioglu, G. Gritsch, Shrishail Patki

Publikováno v: EMBC

A high density wireless electroencephalographic (EEG) platform has been designed. It is able to record up to 64 EEG channels with electrode to tissue impedance (ETI) monitoring. The analog front-end is based on two kinds of low power ASICs implementi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4ddec468694a6d5455970a286e7ba62
https://pubmed.ncbi.nlm.nih.gov/25571308

Spatial correlation based artifact detection for automatic seizure detection in EEG

Autor: Franz Fürbass, A.M. Skupch, Ekaterina Pataraia, Tilmann Kluge, M. Hartmann, Hannes Perko, G. Gritsch, P. Dollfuss, Gerald Lindinger

Publikováno v: EMBC

Automatic EEG-processing systems such as seizure detection systems are more and more in use to cope with the large amount of data that arises from long-term EEG-monitorings. Since artifacts occur very often during the recordings and disturb the EEG-p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9fd9e2f8304af7f9c42f3d6f3c46070
https://pubmed.ncbi.nlm.nih.gov/24110102