Leveraging Machine Learning to Foresee Students’ Stress, Anxiety, and Depression in the COVID-19 Environment
- 12 September 2026
- journal article
- research article
- Published by Springer Nature in Journal of The Institution of Engineers (India): Series B
- p. 1-11
Abstract
No abstract availableKeywords
This publication has 17 references indexed in Scilit:
- A strategic framework for enhancing university rankings based on webometrics criteria: a descriptive-analytical approachDiscover Education, 2025
- Smart web interface for student mental health prediction using machine learning with blockchain technologyNeuroscience Informatics, 2025
- Mental Health Monitoring in Students: A Classifier-Based Machine Learning Approach2025
- Predicting Mental Health Illness using Machine Learning AlgorithmsJournal of Physics: Conference Series, 2022
- Analysis of Machine Learning Algorithms for Predicting Depression2020
- Assessment of Anxiety, Depression and Stress using Machine Learning ModelsProcedia Computer Science, 2020
- Predicting Anxiety, Depression and Stress in Modern Life using Machine Learning AlgorithmsProcedia Computer Science, 2020
- Predicting Depression in Bangladeshi Undergraduates using Machine Learning2019
- Screening of anxiety and depression among the seafarers using machine learning technologyInformatics in Medicine Unlocked, 2019
- Stress, anxiety and depression in heart disease patients: A major challenge for cardiac rehabilitationAnnals of Physical and Rehabilitation Medicine, 2017