A conv-attention encoder-decoder with hand-crafted long-view morphology features reports state-of-the-art EEG and MEG spike classification, including a 13.58-point balanced-accuracy gain on a clinical MEG set.
Development of expert-level automated detection of epileptiform discharges during Electroencephalogram interpretation,
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LV-CadeNet: A Long-View Feature Convolution-Attention Fusion Encoder-Decoder Network for EEG/MEG Spike Analysis
A conv-attention encoder-decoder with hand-crafted long-view morphology features reports state-of-the-art EEG and MEG spike classification, including a 13.58-point balanced-accuracy gain on a clinical MEG set.