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Empowering mental health care with artificial intelligence tool

Koey, Hor Yee (2024) Empowering mental health care with artificial intelligence tool. Final Year Project, UTAR.

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    Abstract

    This project aims to develop an AI-driven mobile application specifically designed to address the pervasive mental health challenges faced by university students, particularly those at UTAR Kampar. It highlights the widespread prevalence of mental health issues within this demographic and explores the transformative potential of Artificial Intelligence (AI) in providing immediate, cost-effective, and non-judgmental support. Through an extensive literature review, the study investigates how AI can help reduce mental health issues and evaluates existing mental health applications, assessing the efficacy of AI technologies in mental health care. The core objective is to create a user-centric, AI-powered mobile application that functions as a virtual companion. This companion offers students a confidential platform to engage in conversations and practice communication skills without the fear of judgment. The application includes features such as sentiment analysis, mental health assessments, and access to helpline and contact information, offering a comprehensive approach to mental health support. These features help users gain insights into their emotional states, assess their mental well-being, and access immediate assistance when needed. By leveraging AI’s capabilities to provide personalized and accessible support, this project aims to enhance the emotional well-being and overall quality of life for university students, while also preparing them for more effective interpersonal interactions.

    Item Type: Final Year Project / Dissertation / Thesis (Final Year Project)
    Subjects: H Social Sciences > H Social Sciences (General)
    Q Science > Q Science (General)
    T Technology > T Technology (General)
    Divisions: Faculty of Information and Communication Technology > Bachelor of Computer Science (Honours)
    Depositing User: ML Main Library
    Date Deposited: 27 Feb 2025 15:10
    Last Modified: 27 Feb 2025 15:10
    URI: http://eprints.utar.edu.my/id/eprint/6980

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