Apriori algorithm based prediction of students’ mental health risks in the context of artificial intelligence
This study demonstrates the potential of AI-powered predictive models for early identification of students at risk of mental health challenges. The findings have significant implications for improving mental health services within higher education institutions. Future research should focus on further refining the model, incorporating real-time data streams, and developing personalized intervention strategies based on the model's predictions.
Authors
- You Fu (ORCID: https://orcid.org/0009-0000-1071-3002)
- Fang Ren (ORCID: https://orcid.org/0000-0002-2251-9220)
- Jiantao Lin (ORCID: https://orcid.org/0000-0001-5705-2299)
Institutions
- Tianjin University (CN)
- Shaanxi Normal University (CN)
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2025-02-12
- DOI
- https://doi.org/10.3389/fpubh.2025.1533934
- Citations
- 6
- Primary Topic
- Mental Health Research Topics
- Type
- article
- Field-Weighted Citation Impact
- 12.71