Hybrid Optimized Focal High-Order Attention Network with Descriptor Computations for Autism Spectrum Disorder Detection in Federated Learning

This paper proposes a federated learning framework combining optimization algorithms with a focal attention neural network for autism spectrum disorder detection from brain imaging data while preserving privacy. The approach achieves 96.83% classification accuracy through functional connectivity analysis and feature selection, demonstrating potential for reliable ASD diagnosis without centralizing sensitive patient data.