A Software-Oriented Deep Learning Framework for Multiclass Academic Stress and Mental Health Risk Prediction
This study proposes a multiclass predictive framework for academic stress and mental health risk classification among students using a Kaggle dataset containing 25,000 records, and indicates that ensemble and deep learning approaches can effectively support multiclass mental health risk classification.