Autism Spectrum Disorder
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in social interaction, communication, and repetitive behaviors, necessitating improved diagnostic and therapeutic approaches. Current research heavily utilizes machine learning, employing diverse model architectures such as transformers, graph neural networks, and convolutional neural networks, to analyze multimodal data including fMRI scans, video recordings of social interactions, and speech patterns. These efforts aim to create objective, efficient diagnostic tools and personalized interventions, ultimately improving the lives of individuals with ASD and informing a deeper understanding of the disorder's neurological underpinnings.
Papers
ViTASD: Robust Vision Transformer Baselines for Autism Spectrum Disorder Facial Diagnosis
Xu Cao, Wenqian Ye, Elena Sizikova, Xue Bai, Megan Coffee, Hongwu Zeng, Jianguo Cao
Spatio-Temporal Attention in Multi-Granular Brain Chronnectomes for Detection of Autism Spectrum Disorder
James Orme-Rogers, Ajitesh Srivastava