AI for Mental Health Support

Access to mental health support is often limited due to stigma, high costs, and a shortage of professionals. Traditional chatbots lack emotional intelligence and fail to provide meaningful assistance. To overcome these limitations, our AI-powered chatbot leverages advanced models like LLaMA, Groq API, and ChromaDB to deliver personalized, empathetic, and context-aware responses. By analyzing user emotions through sentiment detection, the chatbot provides tailored support while maintaining user privacy. It uses retrieval-augmented generation (RAG) for fact-based guidance and integrates mental health resources to enhance user engagement. Past interactions are stored for continuity, ensuring a more personalized experience. Designed to be inclusive, the chatbot supports multiple languages, making it accessible to diverse user groups. With real-time response processing and adaptive learning, it continuously improves its effectiveness. This AI-driven solution bridges the gap between traditional therapy and automated assistance, offering secure, intelligent, and compassionate mental health support.

Authors

Publication Details

Published
2025-04-23
DOI
https://doi.org/10.38124/ijisrt/25apr831
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
0.00
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article

AI for Mental Health Support

S. Anusha, Lakshmi Thangavelu, N. Hiranmayee, P Swetha Kamala et al.
Digital Mental Health Interventions
article

AI for Mental Health Support

S. Anusha, Lakshmi Thangavelu, N. Hiranmayee, P Swetha Kamala, N Sagarika, P Roji Sushma, M Kavya Sri
article en

Abstract

Access to mental health support is often limited due to stigma, high costs, and a shortage of professionals. Traditional chatbots lack emotional intelligence and fail to provide meaningful assistance. To overcome these limitations, our AI-powered chatbot leverages advanced models like LLaMA, Groq API, and ChromaDB to deliver personalized, empathetic, and context-aware responses. By analyzing user emotions through sentiment detection, the chatbot provides tailored support while maintaining user privacy. It uses retrieval-augmented generation (RAG) for fact-based guidance and integrates mental health resources to enhance user engagement. Past interactions are stored for continuity, ensuring a more personalized experience. Designed to be inclusive, the chatbot supports multiple languages, making it accessible to diverse user groups. With real-time response processing and adaptive learning, it continuously improves its effectiveness. This AI-driven solution bridges the gap between traditional therapy and automated assistance, offering secure, intelligent, and compassionate mental health support.

Openalex Percentile: Top 91%
Digital Mental Health Interventions
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