Fig. 9.

Pairwise testing. (A) True positive rates of CNN trained using data from an individual subject. A CNN model was trained using data from each subject on the abscissa and tested using data from other subjects. Of note, the best classification accuracy in pairwise testing outperformed that in leave-one-out testing (cross marks). (B) Classification accuracy matrix. CNN models were trained using data on the abscissa and tested using data on the ordinate. (C) A similarity of seizure patterns among the subjects as visualized by dendrogram based on the classification accuracy in pairwise testing. The performance of the leave-one-out testing (the upper inset) was poor when the distance from any other subject, based on the classification accuracy in pairwise testing, was large.