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DAS-Autism is a Java-based expert system designed to support autism diagnosis using multi-valued logic, linguistic modifiers, and approximate reasoning. It employs a knowledge base of diagnostic symptoms and rules to assess symptom intensity and autism severity, providing explainable results through a graphical user interface.
A wavelet-based Transformer leveraging time-frequency domain cross-attention on rs-fMRI data for Autism Spectrum Disorder (ASD) and ADHD diagnosis. Outperforms competing baselines on ABIDE-I and ADHD-200 (MICCAI '24).