Predicting and Understanding College Student Mental Health with Interpretable Machine Learning
Meghna Roy Chowdhury, Wei Xuan, Shreyas Sen, Yixue Zhao, Yi Ding
Abstract
Mental health issues among college students have reached critical levels, affecting both academic performance and overall wellbeing. Predicting and understanding mental health status among college students is challenging due to three key barriers: the lack of large-scale longitudinal datasets, the prevalence of black-box machine learning models that offer little transparency, and a reliance on population-level analysis rather than personalized understanding.
Topics & Concepts
Mental healthPsychologyApplied psychologyKey (lock)Machine learningArtificial intelligenceMedical educationLongitudinal studyMental modelClinical psychologyComputer scienceMEDLINEBaseline (sea)Machine Learning in HealthcareMental Health via Writing