Ai for predicting student mental health crises: a data-driven approach for early intervention

The rise of mental health crises among students is gradually becoming a menace globally because it does not just affect academic performance but also deep-seated social and personal implications [1;2;3], hence the necessity for innovative solutions. According to the World Health Organization, approximately 20% of teenagers and young adults tend to experience mental health challenges (with a greater portion left undiagnosed or untreated) [ 10] due to a couple of reasons which includes academic pressure, financial concerns, social integration, and uncertainties as it concerns future employment. Conventional evaluation techniques like counsellor-to-student and selfdisclosure; that depends on self-reported surveys and clinical evaluations, often fail to provide timely interventions.