Exploring White Matter Abnormalities in Young Children with Autism Spectrum Disorder: Integrating Multi-shell Diffusion Data and Machine Learning Analysis.
Journal:
Academic radiology
PMID:
38185571
Abstract
RATIONALE AND OBJECTIVES: This study employed tract-based spatial statistics (TBSS) to investigate abnormalities in the white matter microstructure among children with autism spectrum disorder (ASD). Additionally, an eXtreme Gradient Boosting (XGBoost) model was developed to effectively classify individuals with ASD and typical developing children (TDC).