Author

F. Rohani

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Open access Oct 2026

Feature-Engineering Strategies for EEG-Based ADHD Classification in Children: A Controlled Benchmark of Expert, LLM-Guided and Full-Space Comparators

EEG-based machine-learning studies of attention-deficit/hyperactivity disorder (ADHD) are vulnerable to optimistic performance estimates when feature selection or model choice is informed by data outside the training fold. We compared expert-reconstructed, large language model (LLM)-guided and full-space feature strate...

F. Rohani, H. Alhatab, M. Jarrud et al. · medRxiv · 0 citations

#explainable ai Open access Oct 2026

A Multi-Domain EEG Framework Integrating Spectral, Functional Connectivity, and Topological Features for Subject-Level ADHD Classification

Background: Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder characterized by persistent symptoms of inattention, hyperactivity, and impulsivity that significantly affect cognitive, academic, and social functioning. Although electroencephalography (EEG) has emerged as a promising...

F. Rohani, S. Mostafavi, P. Ebrahimifakhar et al. · medRxiv · 0 citations