Machine Learning and Natural Language Processing For Mental Health Analysis

Abstract

Delving into the complexities of mental health issues has transformed into a dynamic exploration, seamlessly integrating the potency of databases and insightful questionnaires. Harnessing the capabilities of Large Language Models, we've crafted a perceptive chatbot that operates in tandem with our website, delivering responses akin to human interaction to user inquiries. Leveraging datasets sourced from Hugging Face pertaining to mental health, we've trained the LLM to generate tailored responses to users' queries, aiding in their mental health analysis. As we scrutinized existing models, we observed that the responses provided lacked depth and human-like nuance. To remedy this, we developed a chatbot designed to bridge this gap, offering more insightful solutions. Coupled with a questionnaire website that facilitates users in understanding their experiences, our chatbot, driven by LLM technology, assists users in navigating and coping with their mental health challenges.