AI-Enhanced Depression Detection and Therapy: Analyzing the VPSYC System

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@article{1706118,
      author = {Ali Husnain, Ayesha Saeed},
      title = {AI-Enhanced Depression Detection and Therapy: Analyzing the VPSYC System},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {2},
      pages = {162-168},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706118.pdf},
      abstract = {Mental health issues, particularly depression, are prevalent and have significant impacts on individuals and society. The stigma associated with mental health, expensive therapy sessions, and a shortage of mental health professionals contribute to the challenge of addressing this issue. This paper presents VPSYC, a web-based conversational chatbot designed to identify the stage of depression, provide therapy, and evaluate changes in sentiment. Utilizing datasets from Counsel Chat, Empathetic Dialogues, and manually created conversations, the VPSYC system leverages transformer models for effective depression analysis and sentiment evaluation. The study demonstrates the effectiveness of the VPSYC system through both automatic and human evaluations, highlighting its potential to provide accessible and robust mental health support.},
      month = {August},
  }