Two neuroanatomical subtypes of males with autism spectrum disorder revealed using semi-supervised machine learning.

ABSTRACT:

Background

Clinical and etiological varieties remain major obstacles to decompose heterogeneity in autism spectrum disorders (ASD). Recently, neuroimaging raised new hope to identify neurosubtypes of ASD for further understanding the biological mechanisms behind the disorder.

Methods

In this study, brain structural MRI data and clinical measures of 221 male subjects with ASD and 257 healthy controls were selected from 7 independent sites from the Autism Brain Image Data Exchange database (ABIDE). Heterogeneity through discriminative analysis (HYDRA), a recently-proposed semi-supervised clustering method was utilized to divide individuals with ASD into several neurosubtypes by regional volumetric measures of gray matter, white matter, and cerebrospinal fluid. Voxel-wise volum

SUBMITTER: Liu G 

PROVIDER: S-EPMC8867630 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature