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In many regions globally, the shortage of trained mental health professionals leaves countless individuals without the support they desperately need. This deficiency, highlighted by the world health organization, underscores the pressing need for innovative solutions to bridge this gap. Chatbots emerged as a scalable intervention, offering an interactive platform for mental health solutions. These systems, adept in spoken, written, and visual languages, hold significant potential, particularly for individuals hesitant to seek traditional mental health services. Even though there are some chatbots already available, like SERMO and Aapka Chikitsak, they still have some problems such as the absence of analyzed reports and graphical data. This paper proposed a new chatbot referred to as YouMatter, to tackle these challenges. Developed on a foundation of advanced natural language processing, and Large Language Model (LLM), YouMatter serves as a mental health care chatbot, extending support and resources to those navigating mental well-being. Leveraging WebSockets, YouMatter facilitates real-time interactions, ensuring assistance is available around the clock. With the capability to analyze users’ mental health trends and present graphical insights, YouMatter empowers individuals to track their progress and receive tailored support. Through personalized email tips and accessible chatbot assistance, YouMatter strives to democratize mental health care, removing barriers and fostering happier, healthier lives for all.
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Stored only when both papers are in the corpus — 13 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.