An Effective LRSF-DLNN-Based Autism Spectrum Disorder Prediction Using EEG and fMRI

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This research proposes a deep learning neural network approach combining logistic regression and scaled functions to improve ASD prediction accuracy using EEG and fMRI neuroimaging data. The method applies signal preprocessing, feature extraction from brain imaging, and optimization algorithms to enhance diagnostic classification performance.