@Article{JICS-15-141, author = {Fei Zheng and Chunzheng Cao}, title = {ADHD Diagnosis and Recognition Based on Functional Classification}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {15}, number = {2}, pages = {141--145}, abstract = { This research starts from the lack of reliable and effective disease identification biomarkers for attention deficit hyperactivity disorder (ADHD). Based on the functional classification methods, including functional generalized linear model (FGLM), functional linear discriminant analysis (FLDA) method and functional principal component analysis (FPCA), we establish models of corpus callosum (CC) shape and give some analyses. The purpose is to verify whether the corpus callosum shape data can be used as an effective classification basis for disease discrimination and classification, and to provide a new auxiliary discriminant diagnosis idea for ADHD disease discrimination. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22389.html} }