AUTHOR=Chen Di , Jia Tianye , Zhang Yuning , Cao Miao , Loth Eva , Lo Chun-Yi Zac , Cheng Wei , Liu Zhaowen , Gong Weikang , Sahakian Barbara Jacquelyn , Feng Jianfeng TITLE=Neural Biomarkers Distinguish Severe From Mild Autism Spectrum Disorder Among High-Functioning Individuals JOURNAL=Frontiers in Human Neuroscience VOLUME=15 YEAR=2021 URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2021.657857 DOI=10.3389/fnhum.2021.657857 ISSN=1662-5161 ABSTRACT=
Several previous studies have reported atypicality in resting-state functional connectivity (FC) in autism spectrum disorder (ASD), yet the relatively small effect sizes prevent us from using these characteristics for diagnostic purposes. Here, canonical correlation analysis (CCA) and hierarchical clustering were used to partition the high-functioning ASD group (i.e., the ASD discovery group) into subgroups. A support vector machine (SVM) model was trained through the 10-fold strategy to predict Autism Diagnostic Observation Schedule (ADOS) scores within the ASD discovery group (