AINeutralarXiv – CS AI · 10h ago6/10
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Explainable AI for Mental Health Prediction in Drug-Affected Populations with Dragonfly Algorithm and GAN Oversampling
Researchers developed an explainable AI framework combining GAN-based oversampling, Dragonfly Algorithm optimization, and XGBoost to predict mental health outcomes in drug-affected populations, achieving 94.17% accuracy. The model addresses class imbalance and interpretability challenges in clinical settings, identifying behavioral factors like sleep quality and emotional regulation as key predictive indicators.