Lukas Alexander Wilhelm Gemein
Lukas Alexander Wilhelm Gemein
PhD Candidate, Neuromedical AI Lab and Neurorobotics Lab, University of Freiburg
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Cited by
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Machine-learning-based diagnostics of EEG pathology
LAW Gemein, RT Schirrmeister, P Chrabąszcz, D Wilson, J Boedecker, ...
NeuroImage 220, 117021, 2020
A reusable benchmark of brain-age prediction from M/EEG resting-state signals
DA Engemann, A Mellot, R Höchenberger, H Banville, D Sabbagh, ...
Neuroimage 262, 119521, 2022
Deep learning with convolutional neural networks for decoding and visualization of eeg pathology
R Tibor Schirrmeister, L Gemein, K Eggensperger, F Hutter, T Ball
arXiv e-prints, arXiv: 1708.08012, 2017
An extended clinical EEG dataset with 15,300 automatically labelled recordings for pathology decoding
AK Kiessner, RT Schirrmeister, LAW Gemein, J Boedecker, T Ball
NeuroImage: Clinical 39, 103482, 2023
Deep Riemannian Networks for EEG Decoding
D Wilson, LAW Gemein, RT Schirrmeister, T Ball
arXiv preprint arXiv:2212.10426, 2022
P64. Deep learning for EEG diagnostics
RT Schirrmeister, L Gemein, K Eggensberger, F Hutter, T Ball
Clinical Neurophysiology 129 (8), e94, 2018
Brain Age Revisited: Investigating the State vs. Trait Hypotheses of EEG-derived Brain-Age Dynamics with Deep Learning
LAW Gemein, RT Schirrmeister, J Boedecker, T Ball
arXiv preprint arXiv:2310.07029, 2023
Supervised machine learning approaches applied in the diagnostic workup of spontaneous intracranial hypotension
LM Kraus, C Fung, L Dieringer, L Gemein, T Ball, J Beck
Brain and Spine 1, 100835, 2021
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