id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-31263	Bai, Junming; Hou, Bingxu; Wu, Jiansheng	ADHD-Conformer: EEG-Based Classification and Detection of ADHD	2025	3	.pdf	application/pdf	1241	89	34	The proposed ADHD-Conformer is a hybrid deep neural network designed specifically for modeling the spatiotemporal characteristics of EEG signals in the context of ADHD diagnosis. This study presents an innovative deep learning approach that enhances both the accuracy and generalization of ADHD classification from EEG data.	cache/fcis-31263.pdf	txt/fcis-31263.txt