Classification of autism spectrum disorder using electroencephalography in Chinese children: a cross-sectional retrospective study.

ABSTRACT: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by diverse clinical features. EEG biomarkers such as spectral power and functional connectivity have emerged as potential tools for enhancing early diagnosis and understanding of the neural processes underlying ASD. However, existing studies yield conflicting results, necessitating a comprehensive, data-driven analysis. We conducted a retrospective cross-sectional study involving 246 children with ASD and 42 control children. EEG was collected, and diverse EEG features, including spectral power and spectral coherence were extracted. Statistical inference methods, coupled with machine learning models, were employed to identify differences in EEG features between ASD and control groups and develop classifi

SUBMITTER: Ke SY 

PROVIDER: S-EPMC10850305 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature