Dynamic Spatio-Temporal Graph Neural Network for Early Detection of Pornography Addiction in Adolescents Based on Electroencephalogram Signals

Researchers developed a Dynamic Spatio-Temporal Graph Neural Network (DST-GNN) using EEG signals to detect pornography addiction in adolescents, achieving 71% F1-score with 85.71% recall. The AI system identifies brain connectivity patterns as objective biomarkers, representing a significant advancement in neurobiological detection methods.