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@article{186684,
        author = {Priyanka Pandit Mali and Madhura Sanjay Limje and Shweta Ganeshrao Sonar and Omkar Raju Lohat and Prof. Aarti Bhujbal},
        title = {SURVEY-BASED MENTAL HEALTH CHATBOT USING NLP AND FLASK FRAMEWORK},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {1502-1504},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186684},
        abstract = {Mental health issues are increasingly prevalent, and timely detection is crucial for providing support. This paper presents a Mental Health Detection Chatbot that leverages Natural Language Processing (NLP) techniques and survey data to identify potential mental health conditions in users. The chatbot is developed using Python, Flask, and NLTK, with SQLite as the backend database. Survey data collected from users is analyzed to improve the chatbot’s response accuracy and classification of mental health conditions. Experimental results demonstrate that the system effectively identifies mental health concerns and provides appropriate guidance, highlighting its potential as an accessible mental health support tool.},
        keywords = {Mental Health, Chatbot, NLP, Survey Analysis, Python, NLTK, Flask, SQLite, Mental Health Detection},
        month = {November},
        }