TY - JOUR
T1 - ADHD Diagnosis and Recognition Based on Functional Classification
AU - Fei Zheng and Chunzheng Cao
JO - Journal of Information and Computing Science
VL - 2
SP - 141
EP - 145
PY - 2020
DA - 2020/06
SN - 15
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22389.html
KW - 
AB -  This research starts from the lack of reliable &nbsp;and effective disease identification biomarkers for 
attention &nbsp;deficit &nbsp;hyperactivity &nbsp;disorder &nbsp;(ADHD). &nbsp;Based &nbsp;on &nbsp;the &nbsp;functional &nbsp;classification &nbsp;methods, &nbsp;including 
functional &nbsp;generalized &nbsp;linear &nbsp;model &nbsp;(FGLM), &nbsp;functional &nbsp;linear &nbsp;discriminant &nbsp;analysis &nbsp;(FLDA) &nbsp;method &nbsp;and 
functional &nbsp;principal &nbsp;component &nbsp;analysis &nbsp;(FPCA), &nbsp;we &nbsp;establish &nbsp;models &nbsp;of &nbsp;corpus &nbsp;callosum &nbsp;(CC) &nbsp;shape &nbsp;and 
give &nbsp;some &nbsp;analyses. &nbsp;The &nbsp;purpose &nbsp;is &nbsp;to &nbsp;verify &nbsp;whether &nbsp;the &nbsp;corpus &nbsp;callosum &nbsp;shape &nbsp;data &nbsp;can &nbsp;be &nbsp;used &nbsp;as &nbsp;an 
effective &nbsp;classification &nbsp;basis &nbsp;for &nbsp;disease &nbsp;discrimination &nbsp;and &nbsp;classification, &nbsp;and &nbsp;to &nbsp;provide &nbsp;a &nbsp;new &nbsp;auxiliary 
discriminant diagnosis idea for ADHD disease discrimination.