Before revision:  The labels were given to paroxysmal discharges visually observed in both ictal (seizure) and interictal (nonseizure) intervals . Results showed that the mEEGNet detected abnormal EEGs with the area under the curve, F1-values, and sensitivity equivalent to or higher than those of existing CNNs. Moreover, the number of parameters is much smaller than other CNN models.
After revision:  The labels were given to paroxysmal discharges visually observed in both ictal (seizure) and interictal (nonseizure) intervals . Results showed that the mEEGNet detected abnormalities with the area under the curve, F1-values, and sensitivity equivalent to or higher than those of existing CNNs. Moreover, the number of parameters is much smaller than other CNN models.