@article{4435,
  author = {Ling Pan,Haili Ma,Yongqiang Li},
  title = {Design of a Deep Learning-Based Psychological Counseling System for College Students' Mental Health},
  journal = {Journal of E-Technology},
  year = {2025},
  volume = {16},
  number = {2},
  doi = {https://doi.org/10.6025/jet/2025/16/2/64-71},
  url = {https://www.dline.info/jet/fulltext/v16n2/jetv16n2_3.pdf},
  abstract = {In response to the necessity of psychological counselling for college student's mental health, this paper proposes a psychological counselling and assessment system based on PGCapsNet. The system aims to achieve both college students' psychological health assessment and real-time online counseling, while improving the accuracy of predicting their mental health status. Having an experienced psychological counsellor is crucial for college students' mental health and crisis management. The simulation results demonstrate that compared to other models, using the PGCapsNet model can effectively improve the levels of precision, recall, F1-measure, and accuracy of the college student psychological counseling system, achieving 70%, 75%, 72%, and 74%, respectively. This validates the feasibility and superiority of this design. This paper discusses a novel algorithm that combines capsule networks and convolutional neural networks, incorporating dynamic routing algorithms and deep learning capabilities.},
}