Application of Explainable AI in Neuroscience: Enhancing Autism Screening
This study demonstrates that a ResNet+BiLSTM hybrid deep network, enhanced with SHAP and LIME explainable AI techniques, can accurately distinguish children with autism from neurotypical subjects using EEG and ERP biomarkers while providing transparent insights into the model's decision-making process.