Classifying ASD based on time-series fMRI using spatial–temporal transformer

• Published in: Computers in biology and medicine Vol. 151; no. Pt B; p. 106320
• Main Authors: Deng, Xin, Zhang, Jiahao, Liu, Rui, Liu, Ke
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.12.2022; Elsevier Limited
• Subjects: ABIDE; Adversarial Generation Network(GAN); Autism; Autism spectrum disorder (ASD); Autism Spectrum Disorder - diagnostic imaging; Biomarkers; Brain - diagnostic imaging; Datasets; Deep learning; Deep learning(DL); Diagnosis; Endoscopy; Functional magnetic resonance imaging; Functional magnetic resonance imaging (fMRI); Humans; Internal Medicine; Machine learning; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Medical imaging; Neuroimaging; Other; Spatial discrimination learning; Time Factors; Transformer; Transformers; Deep learning(DL); ABIDE; Transformer; Functional magnetic resonance imaging (fMRI); Autism spectrum disorder (ASD); Adversarial Generation Network(GAN)

As the prevalence of autism spectrum disorder (ASD) increases globally, more and more patients need to receive timely diagnosis and treatment to alleviate their suffering. However, the current diagnosis method of ASD still adopts the subjective symptom-based criteria through clinical observation, wh...