DCDA-Net: A depthwise convolution dilated attention network with temporal weighted loss for seizure prediction

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24 Oct 2026 0 comments

The sudden and unforeseeable nature of seizures poses serious threats to patients' safety and quality of daily life, making the development of highly accurate and reliable seizure prediction methods of significant clinical importance. To this end, this study proposed a seizure prediction model by integrating depthwise convolution and a novel dilated attention mechanism, named DCDA-Net. Depthwise convolution was first employed to extract features from each EEG channel independently, preserving...