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@article{171320,
        author = {Muskan Wankar and Muskan Fakir and Ayeshasiddiqa Shaikh and Kalyani Gaikwad and Prof. R. A. Bhartiya},
        title = {Mental health status prediction/monitoring app},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {3847-3849},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171320},
        abstract = {Mental health issues have become a significant concern globally, necessitating advanced systems to assess and promote mental well-being. This review examines a Mental Health Prediction System, a user-centric software designed to assess mental health, provide valuable resources, and offer personalized suggestions. The system incorporates four essential modules: Mental Health Prediction, Articles and Blogs, Symptoms and Suggestions, and an AI-powered chatbot, "Ask AI." It employs Python, MySQL, and machine learning algorithms like Logistic Regression and Random Forest for effective mental health assessment. This paper discusses the functionalities, technologies, and implications of the system while suggesting future enhancements for broader applications.},
        keywords = {},
        month = {December},
        }