Review Paper on “Jarvie: AI-Driven Mental Health Companion”

Abstract

With the growing prevalence of mental health issues, many individuals still face barriers to accessing timely and effective support. This paper presents an innovative AI-powered Mental Health Companion aimed at providing personalized, real-time mental health assistance. By utilizing advanced natural language processing (NLP) techniques and machine learning models, the system interacts with users through meaningful conversations, offering customized coping strategies, mood tracking, and resource recommendations. The solution incorporates techniques such as sentiment analysis and adaptive learning to continuously refine responses based on user behavior and emotional states. The companion's effectiveness will be measured through metrics including user engagement, response accuracy, and its impact on emotional well-being. This scalable, on- demand tool offers the potential to significantly expand access to mental health support, reducing the strain on traditional services. Keywords - Artificial Intelligence, Mental Health, Natural Language Processing (NLP), Machine Learning, Chatbot, Mental Health Companion, Sentiment Analysis, Conversational AI, Generative AI.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 1 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.