School of Computer Science and Engineering Researcher Publishes New Study Findings on Diagnostics (Enhancing Diagnostic Decision-Making: Ensemble Learning Techniques for Reliable Stress Level Classification).

A recent study conducted by researchers at the School of Computer Science and Engineering in Chennai, India, explores the impact of academic pressure on student stress levels. The study proposes an ensemble learning approach to classify stress levels based on factors such as sleep hours, screen time, and assignment completion. The results show that the model achieved an accuracy of 93.48% and an F1 score of 93.14% in predicting stress levels. By identifying areas for improvement, students can reduce their stress levels and make their academic lifestyles more effective. [Extracted from the article]