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1712354PublishedVol 9 · Issue 5

Real-Time AI-Enhanced Chatbots for Mental Health Support

Khushi Rajput Komal Nilesh Kumar Pandey Dr. Ishrat Ali Prof. (Dr.) Sanjay Pachauri

Subject area: Science,Engineering and Technology  ·  Area of research: AI in Healthcare

DOI: https://doi.org/10.64388/IREV9I5-1712354

Abstract

Mental health disorders represent one of the most pressing global health challenges of our time, contributing significantly to the worldwide disease burden and economic losses. Traditional therapeutic approaches struggle to meet the escalating demand for mental health services, leaving millions without adequate care. This research paper explores the transformative potential of AI-enhanced chatbots in revolutionizing mental health support systems. By leveraging Natural Language Processing (NLP), sentiment analysis, and emotion recognition technologies, these intelligent systems provide scalable, accessible, and stigma-free support available 24/7. This paper examines the architecture, technologies, key features, benefits, and ethical considerations of real-time AI chatbots designed for mental health applications. The findings demonstrate that while these systems cannot replace human therapists, they serve as crucial bridges to professional care, significantly improving accessibility and early intervention capabilities.

Keywords

Artificial Intelligence, Chatbots, Mental Health, NLP, Sentiment Analysis, Healthcare Technology, Digital Therapeutics

How to cite this paper

Khushi Rajput, Komal, Nilesh Kumar Pandey, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri "Real-Time AI-Enhanced Chatbots for Mental Health Support" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 2086-2093 https://doi.org/10.64388/IREV9I5-1712354
Khushi Rajput, Komal, Nilesh Kumar Pandey, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri "Real-Time AI-Enhanced Chatbots for Mental Health Support" Iconic Research And Engineering Journals, vol. 9, no. 5, Dec. 2025, doi: https://doi.org/10.64388/IREV9I5-1712354
Khushi Rajput, Komal, Nilesh Kumar Pandey, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri (2025). Real-Time AI-Enhanced Chatbots for Mental Health Support. Iconic Research And Engineering Journals, 9(5). doi: https://doi.org/10.64388/IREV9I5-1712354
Khushi Rajput, Komal, Nilesh Kumar Pandey, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri "Real-Time AI-Enhanced Chatbots for Mental Health Support" Iconic Research And Engineering Journals, vol. 9, no. 5, Dec. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1712354
@article{1712354,
      author = {Khushi Rajput, Komal, Nilesh Kumar Pandey, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri},
      title = {Real-Time AI-Enhanced Chatbots for Mental Health Support},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {5},
      pages = {2086-2093},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712354.pdf},
      abstract = {Mental health disorders represent one of the most pressing global health challenges of our time, contributing significantly to the worldwide disease burden and economic losses. Traditional therapeutic approaches struggle to meet the escalating demand for mental health services, leaving millions without adequate care. This research paper explores the transformative potential of AI-enhanced chatbots in revolutionizing mental health support systems. By leveraging Natural Language Processing (NLP), sentiment analysis, and emotion recognition technologies, these intelligent systems provide scalable, accessible, and stigma-free support available 24/7. This paper examines the architecture, technologies, key features, benefits, and ethical considerations of real-time AI chatbots designed for mental health applications. The findings demonstrate that while these systems cannot replace human therapists, they serve as crucial bridges to professional care, significantly improving accessibility and early intervention capabilities.},
      keywords = {Artificial Intelligence, Chatbots, Mental Health, NLP, Sentiment Analysis, Healthcare Technology, Digital Therapeutics},
      month = {November},
      doi = {https://doi.org/10.64388/IREV9I5-1712354}
  }