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@article{205690,
        author = {Shlok Ekhande and Shubham Kamble and Sagar Ingole and Roshan Jaybhaye and Prof. A. A. Bamanikar},
        title = {AI-Based Mental Health Detection and Recommendation Platform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {7366-7374},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205690},
        abstract = {Mental health is an essential part of a person’s overall well-being, but in today’s fast-paced and stressful lifestyle, many individuals face emotional problems such as stress, anxiety, sadness, and mood fluctuations. Due to lack of awareness, busy schedules, and limited access to mental health support, these issues often go unnoticed and untreated. The AI-Powered Mental Health Monitoring and Recommendation System is a web-based application developed to help users monitor and improve their emotional well-being using Artificial Intelligence and Machine Learning techniques. The system interacts with users through dynamically generated daily questions using the Gemini API, allowing users to express their thoughts, feelings, and daily experiences. The collected responses are processed using Natural Language Processing (NLP) techniques such as tokenization, stopword removal, lowercase conversion, and TF-IDF feature extraction. A trained Machine Learning model then analyzes the processed text and predicts the emotional state of the user, such as Happy, Sad, Stressed, or Relaxed. Based on the predicted emotion, the system provides personalized video recommendations including motivational, meditation, relaxation, and entertainment content to support emotional improvement and mental wellness. The application also stores user responses, predicted emotions, and timestamps in a database, enabling users to view their emotional history and track mood patterns over time. Additionally, graphical visualizations are generated to help users understand emotional trends and identify changes in their mental condition. Developed using Flask, Python, Machine Learning, and AI technologies, the proposed system offers a simple, interactive, and user-friendly platform that promotes mental health awareness, self-monitoring, and emotional self-care through intelligent analysis and personalized recommendations.},
        keywords = {Artificial Intelligence (AI), Machine Learning (ML), Mental Health Monitoring, Natural Language Processing (NLP), Emotion Detection, Recommendation System, Gemini API, Flask Web Application.},
        month = {June},
        }