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SMOTE-VAR: An Uncertainty-Aware Oversampling Method for Predicting Depression Remission in University Students

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

University students experience disproportionately high rates of common mental health conditions, such as depression, which can impair learning, social functioning, and overall well-being. Although lifestyle interventions such as mindfulness and physical activity can reduce the symptoms, many do not achieve symptomatic remission. Developing new approaches to identify students with poor outcomes could enable earlier and more targeted intervention. Machine learning (ML) methods have increasingly been used to predict remission in depressive patients. However, these ML models often suffer from clas

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