ADHD Diagnosis and Recognition Based on Functional Classification

Abstract

This research starts from the lack of reliable \u00a0and effective disease identification biomarkers for attention \u00a0deficit \u00a0hyperactivity \u00a0disorder \u00a0(ADHD). \u00a0Based \u00a0on \u00a0the \u00a0functional \u00a0classification \u00a0methods, \u00a0including functional \u00a0generalized \u00a0linear \u00a0model \u00a0(FGLM), \u00a0functional \u00a0linear \u00a0discriminant \u00a0analysis \u00a0(FLDA) \u00a0method \u00a0and functional \u00a0principal \u00a0component \u00a0analysis \u00a0(FPCA), \u00a0we \u00a0establish \u00a0models \u00a0of \u00a0corpus \u00a0callosum \u00a0(CC) \u00a0shape \u00a0and give \u00a0some \u00a0analyses. \u00a0The \u00a0purpose \u00a0is \u00a0to \u00a0verify \u00a0whether \u00a0the \u00a0corpus \u00a0callosum \u00a0shape \u00a0data \u00a0can \u00a0be \u00a0used \u00a0as \u00a0an effective \u00a0classification \u00a0basis \u00a0for \u00a0disease \u00a0discrimination \u00a0and \u00a0classification, \u00a0and \u00a0to \u00a0provide \u00a0a \u00a0new \u00a0auxiliary discriminant diagnosis idea for ADHD disease discrimination.